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PROBABILITY AND STATISTICS BY ENGR. JORGE P. BAUTISTA

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PROBABILITY AND STATISTICS

BYENGR. JORGE P. BAUTISTA

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COURSE OUTLINE

I. Introduction to StatisticsII. Tabular and Graphical representation of

DataIII. Measures of Central Tendencies, Locations

and VariationsIV. Measure of Dispersion and CorrelationV. Probability and CombinatoricsVI. Discrete and Continuous DistributionsVII.Hypothesis Testing

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Text and References

Statistics: a simplified approach by Punsalan and Uriarte, 1998, Rex Texbook

Probability and Statistics by Johnson, 2008, Wiley

Counterexamples in Probability and Statistics by Romano and Siegel, 1986, Chapman and Hall

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Introduction to Statistics

Definition1.In its plural sense, statistics is a set of

numerical data e.g. Vital statistics, monthly sales, exchange rates, etc.

2.In its singular sense, statistics is a branch of science that deals with the collection, presentation, analysis and interpretation of data.

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General uses of Statistics

a. Aids in decision making by providing comparison of data, explains action that has taken place, justify a claim or assertion, predicts future outcome and estimates un known quantities

b. Summarizes data for public use

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Examples on the role of Statistics- In Biological and medical sciences, it helps researchers

discover relationship worthy of further attention.Ex. A doctor can use statistics to determine to what

extent is an increase in blood pressure dependent upon age

- In social sciences, it guides researchers and helps them support theories and models that cannot stand on rationale alone.

Ex. Empirical studies are using statistics to obtain socio-economic profile of the middle class to form new socio-political theories.

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Con’t- In business, a company can use statistics to

forecast sales, design products, and produce goods more efficiently.

Ex. A pharmaceutical company can apply statistical procedures to find out if the new formula is indeed more effective than the one being used.

- In Engineering, it can be used to test properties of various materials,

- Ex. A quality controller can use statistics to estimate the average lifetime of the products produced by their current equipment.

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Fields of Statistics

a. Statistical Methods of Applied Statistics:1. Descriptive-comprise those methods concerned

with the collection, description, and analysis of a set of data without drawing conclusions or inferences about a larger set.

2. Inferential-comprise those methods concerned with making predictions or inferences about a larger set of data using only the information gathered from a subset of this larger set.

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con’t

b. Statistical theory of mathematical statistics- deals with the development and exposition of theories that serve as a basis of statistical methods

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Descriptive VS Inferential

DESCRIPTIVE• A bowler wants to find his

bowling average for the past 12 months

• A housewife wants to determine the average weekly amount she spent on groceries in the past 3 months

• A politician wants to know the exact number of votes he receives in the last election

INFERENTIALA bowler wants to estimate his

chance of winning a game based on his current season averages and the average of his opponents.

A housewife would like to predict based on last year’s grocery bills, the average weekly amount she will spend on groceries for this year.

A politician would like to estimate based on opinion polls, his chance for winning in the upcoming election.

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Population as Differrentiated from Sample

The word population refers to groups or aggregates of people, animals, objects, materials, happenings or things of any form, this means that there are populations of students, teachers, supervisors, principals, laboratory animals, trees, manufactured articles, birds and many others. If your interest is on few members of the population to represent their characteristics or traits, these members constitute a sample. The measures of the population are called parameters, while those of the sample are called estimates or statistics.

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The Variable

It refers to a characteristic or property whereby the members of the group or set vary or differ from one another. However, a constant refers to a property whereby the members of the group do not differ one another.

Variables can be according to functional relationship which is classified as independent and dependent. If you treat variable y as a function of variable z, then z is your independent variable and y is your dependent variable. This means that the value of y, say academic achievement depends on the value of z.

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Con’t

Variables according to continuity of values.1. Continuous variable – these are variables

whose levels can take continuous values. Examples are height, weight, length and width.

2. Discrete variables – these are variables whose values or levels can not take the form of a decimal. An example is the size of a particular family.

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Con’t

Variables according to scale of measurements:1. Nominal – this refers to a property of the

members of a group defined by an operation which allows making of statements only of equality or difference. For example, individuals can be classified according to thier sex or skin color. Color is an example of nominal variable.

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Con’t2. Ordinal – it is defined by an operation whereby

members of a particular group are ranked. In this operation, we can state that one member is greater or less that the others in a criterion rather than saying that he/it is only equal or different from the others such as what is meant by the nominal variable.

3. Interval – this refers to a property defined by an operation which permits making statement of equality of intervals rather than just statement of sameness of difference and greater than or less than. An interval variable does not have a “true” zero point.; althought for convenience, a zero point may be assigned.

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Con’t

4. Ratio – is defined by the operation which permits making statements of equality of ratios in addition to statements of sameness or difference, greater than or less than and equality or inequality of differences. This means that one level or value may be thought of or said as double, triple or five times another and so on.

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Assignment no. 1

I. Make a list of at least 5 mathematician or scientist that contributes in the field of statistics. State their contributions

II. With your knowledge of statistics, give a real life situation how statistics is applied. Expand your answer.

III. When can a variable be considered independent and dependent? Give an example for your answer.

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Con’t

IV. Enumerate some uses of statistics. Do you think that any science will develop without test of the hypothesis? Why?

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Examples of Scales of Measurement

1.Nominal LevelEx. Sex: M-Male F-Female Marital Status: 1-single 2- married 3-

widowed 4- separated2. Ordinal LevelEx. Teaching Ratings: 1-poor 2-fair 3- good 4-

excellent

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Con’t3. Interval LevelEx. IQ, temperature4. Ratio LevelEx. Age, no. of correct answers in exam

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Data Collection Methods

1. Survey Method – questions are asked to obtain information, either through self administered questionnaire or personal interview.

2. Observation Method – makes possible the recording of behavior but only at the time of occurrence (ex. Traffic count, reactions to a particular stimulus)

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Con’t3. Experimental method – a method designed for

collecting data under controlled conditions. An experiment is an operation where there is actual human interference with the conditions that can affect the variable under study.

4. Use of existing studies – that is census, health statistics, weather reports.

5. Registration method – that is car registration, student registration, hospital admission and ticket sales.

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Tabular Representation

Frequency Distribution is defined as the arrangement of the gathered data by categories plus their corresponding frequencies and class marks or midpoint. It has a class frequency containing the number of observations belonging to a class interval. Its class interval contain a grouping defined by the limits called the lower and the upper limit. Between these limits are called class boundaries.

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Frequency of a Nominal DataMale and Female College students

Major in Chemistry

SEX FREQUENCY

MALE 23

FEMALE 107

TOTAL 130

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Frequency of Ordinal DataEx. Frequency distribution of Employee Perception on

the Behavior of their Administrators

Perception Frequency

Strongly favorable 10

favorable 11

Slightly favorable 12

Slightly unfavorable 14

Unfavorable 22

Strongly unfavorable 31

total 100

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Frequency Distribution Table

Definition:1. Raw data – is the set of data in its original

form2. Array – an arrangement of observations

according to their magnitude, wither in increasing or decreasing order.

Advantages: easier to detect the smallest and largest value and easy to find the measures of position

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Grouped Frequency of Interval Data

Given the following raw scores in Algebra Examination,

47 56 42 28 56 41 56 55 5978 50 55 57 38 62 52 66 6579 33 34 37 47 42 68 62 5480 68 48 56 39 77 80 62 7157 52 60 70

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1. Compute the range: R = H – L and the number of classes by K = 1 + 3.322log n where n = number of observations.

2. Divide the range by 10 to 15 to determine the acceptable size of the interval. Hint: most frequency distribution have odd numbers as the size of the interval. The advantage is that the midpoints of the intervals will be whole number.

3. Organize the class interval. See to it that the lowest interval begins with a number that is multiple of the interval size.

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4. Tally each score to the category of class interval it belongs to.

5. Count the tally columns and summarizes it under column (f). Then add the frequency which is the total number of the cases (N).

6. Determine the class boundaries. UCB and LCB.(upper and lower class boundary)

7. Compute the midpoint for each class interval and put it in the column (M).

M = (LS + HS) / 2

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8. Compute the cumulative distribution for less than and greater than and put them in column cf< and cf>. (you can now interpret the data). cf = cumulative frequency

9. Compute the relative frequency distribution. This can be obtained by

RF% = CF/TF x 100% CF = CLASS FREQUENCY TF = TOTAL FREQUENCY

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Graphical RepresentationThe data can be graphically

presented according to their scale or level of measurements.

1. Pie chart or circle graph. The pie chart at the right is the enrollment from elementary to master’s degree of a certain university. The total population is 4350 students

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2. Histogram or bar graph- this graphical representation can be used in nominal, ordinal or interval. For nominal bar graph, the bars are far apart rather than connected since the categories are not continuous. For ordinal and interval data, the bars should be joined to emphasize the degree of differences

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Given the bar graph of how students rate their library.

A-strongly favorable, 90B-favorable, 48C-slightly favorable, 88D-slightly unfavorable, 48E-unfavorable, 15F-strongly unfavorable, 25

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The Histogram of Person’s Age with Frequency of Travel

age freq RF

19-20 20 39.2%

21-22 21 41.2%

23-24 4 7.8%

25-26 4 7.8%

27-28 2 3.9%

total 51 100%

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ExercisesFrom the previous grouped data on algebra scores,a. Draw its histogram using the frequency in the y axis

and midpoints in the x axis.b. Draw the line graph or frequency polygon using

frequency in the y axis and midpoints in the x axis.c. Draw the less than and greater than ogives of the

data. Ogives is a cumulation of frequencies by class intervals. Let the y axis be the CF> and x axis be LCB while y axis be CF< and x axis be UCB

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Con’td. Plot the relative frequency using the y axis as

the relative frequency in percent value while in the x axis the midpoints.

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25 30 35 40 45 50 55 60 65 70 75 80 85 90

9

8

7

6

5

4

3

2

1

0

f

midpoint29.5 - UCB27- midpoint24.5 - LCB

midpoint

HISTOGRAMLINE GRAPH

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29.5 34.5 39.5 44.5 49.5 54.5 59.5 64.5 69.5 74.5 79.5 84.5

cf less than

40

35

30

25

20

15

10

5

0

UCB

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40

35

30

25

20

15

10

5

024.5 29.5 34.5 39.5 44.5 49.5 54.5 59.5 64.5 69.5 74.5 79.5

cf greater than

LCB

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Assignment No. 2Given the score in a statistics examinations,33 38 56 35 70 44 81 44 8047 45 72 45 50 51 51 52 6654 54 53 56 84 58 56 57 7055 56 39 56 59 72 63 89 6360 69 65 61 62 64 64 69 6065 53 66 66 67 67 68 68 6966 66 67 70 59 40 71 73 6073 73 73 73 73 73 74 73 7374 79 74 74 70 73 46 74 7475 74 75 75 76 55 77 78 7379 48 81 44 84 77 88 63 8573

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1. Construct the class interval, frequency table, class midpoint(use a whole number midpoint), less than and greater than cumulative frequency, upper and lower boundary and relative frequency.

2. Plot the histogram, frequency polygon, and ogives

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3. Draw the pie chart and bar graph of the plans of computer science students with respect to attending a seminar. Compute for the Relative frequency of each.

A-will not attend=45B-probably will not attend=30C-probably will attend=40D-will attend=25

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Measures of Centrality and Location

Mean for Ungrouped DataX’ = ΣX / N where X’ = the mean ΣX = the sum of all scores/data N = the total number of casesMean for Grouped DataX’ = ΣfM / N where X’ = the mean M = the midpoint fM = the product of the frequency and each

midpoint N = total number of cases

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Ex. 1. Find the mean of 10, 20, 25,30, 30, 35, 40 and 50.2. Given the grades of 50 students in a statistics classClass interval f 10-14 4 15-19 3 20-24 12 25-29 10 30-34 6 35-39 6 40-44 6 45-49 3

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The weighted mean. The weighted arithmetic mean of given groups of data is the average of the means of all groups

WX’ = ΣXw / N where WX’ = the weighted mean w = the weight of X ΣXw = the sum of the weight of X’s N = Σw = the sum of the weight of

X

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Ex.Find the weighted mean of four groups of

means below:Group, i 1 2 3 4Xi 60 50 70 75

Wi 10 20 40 50

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Median for Ungrouped DataThe median of ungrouped data is the

centermost scores in a distribution. Mdn = (XN/2 + X (N + 2)/2) / 2 if N is even

Mdn = X (1+N)/2 if N is oddEx. Find the median of the following sets of

score:Score A: 12, 15, 19, 21, 6, 4, 2Score B: 18, 22, 31, 12, 3, 9, 11, 8

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Median for Grouped DataProcedure:1. Compute the cumulative frequency less than.2. Find N/23. Locate the class interval in which the middle class falls, and

determine the exact limit of this interval.4. Apply the formula Mdn = L + [(N/2 – F)i]/fm where L = exact lower limit interval containing

the median class F = The sum of all frequencies preceeding L. fm = Frequency of interval containing the median

class i = class interval N = total number of cases

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Ex. Find the median of the given frequency table.class interval f cf<25-29 3 330-34 5 835-39 10 1840-44 15 3345-49 15 4850-54 15 6355-59 21 8460-64 8 9265-69 6 9870-74 2 100

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Mode of Ungrouped DataIt is defined as the data value or specific score

which has the highest frequency.Find the mode of the following data.Data A : 10, 11, 13, 15, 17, 20Data B: 2, 3, 4, 4, 5, 7, 8, 10Data C: 3.5, 4.8, 5.5, 6.2, 6.2, 6.2, 7.3, 7.3, 7.3,

8.8

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Mode of Grouped DataFor grouped data, the mode is defined as the midpoint

of the interval containing the largest number of cases.

Mdo = L + [d1/(d1 + d2)]i where L = exact lower limit interval

containing the modal class. d1 = the difference of the modal class and the

frequency of the interval preceding the modal class d2 = the difference of the modal class and the

frequency of the interval after the modal class.

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Ex. Find the mode of the given frequency table.class interval f cf<25-29 3 330-34 5 835-39 10 1840-44 15 3345-49 15 4850-54 15 6355-59 21 8460-64 8 9265-69 6 9870-74 2 100

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Exercises 1. Determine the mean, median and mode of

the age of 15 students in a certain class.15, 18, 17, 16, 19, 18, 23 , 24, 18, 16, 17, 20, 21,

192. To qualify for scholarship, a student should

have garnered an average score of 2.25. determine if the a certain student is qualified for a scholarship.

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Subjectno. of units grade A 1 2.0 B 2 3.0 C 3 1.5 D 3 1.25 E 5 2.0

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3. Find the mean, median and mode of the given grouped data.

Classes f 11-22 223-34 835-46 1147-58 1959-70 1471-82 583-94 1

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Quartiles refer to the values that divide the distribution into four equal parts. There are 3 quartiles represented by Q1 , Q2 and Q3. The value Q1 refers to the value in the distribution that falls on the first one fourth of the distribution arranged in magnitude. In the case of Q2 or the second quartile, this value corresponds to the median. In the case of third quartile or Q3, this value corresponds to three fourths of the distribution.

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LH

Q3

Q2

Q1= 1st quartile

= 2nd quartile

=3rd quartile

The position of the quartiles in a given set of data

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For grouped data, the computing formula of the kth quartile where k = 1,2,3,4,… is given by

Qk = L + [(kn/4 - F)/fm]IiWhere L = lower class boundary of the kth

quartile class F = cumulative frequency before the kth

quartile class fm = frequency before the kth quartile i = size of the class interval

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ExercisesCompute the value of the first and third quartile of the given

dataclass interval f cf<25-29 3 330-34 5 835-39 10 1840-44 15 3345-49 15 4850-54 15 6355-59 21 8460-64 8 9265-69 6 9870-74 2 100

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Decile:If the given data is divided into ten equal parts,

then we have nine points of division known as deciles. It is denoted by D1 , D2,

D3 , D4 …and D9

Dk = L + [(kn/10 – F)/fm] I

Where k = 1,2,3,4 …9

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Exercises Compute the value of the third, fifth and seventh decile of the

given dataclass interval f cf<25-29 3 330-34 5 835-39 10 1840-44 15 3345-49 15 4850-54 15 6355-59 21 8460-64 8 9265-69 6 9870-74 2 100

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Percentile- refer to those values that divide a distribution into one hundred equal parts. There are 99 percentiles represented by P1, P2, P3, P4, P5, …and P99. when we say 55th percentile we are referring to that value at or below 55/100 th of the data.

Pk = L + [(kn/100 – F)/fm]i

Where k = 1,2,3,4,5,…99

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Exercises Compute the value of the 30th, 55th, 68th and 88th percentile of

the given dataclass interval f cf<25-29 3 330-34 5 835-39 10 1840-44 15 3345-49 15 4850-54 15 6355-59 21 8460-64 8 9265-69 6 9870-74 2 100

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Assignment no. 3I. The rate per hour in pesos of 12 employees

of a certain company were taken and are shown below.

44.75, 44.75, 38.15, 39.25, 18.00, 15.75, 44.75, 39.25, 18.50, 65.25, 71.25, 77.50

a. Find the mean, median and mode.b. If the value 15.75 was incorrectly written as

45.75, what measure of central tendency will be affected? Support your answer.

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II. The final grades of a student in six subjects were tabulated below.

Subj units final gradeAlgebra 3 60Religion 2 90English 3 75Pilipino 3 86PE 1 98History 3 70a. Determine the weighted meanb. If the subjects were of equal number of units, what

would be his average?

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III. The ages of qualified voters in a certain barangay were taken and are shown below

Class Interval Frequency18-23 2024-29 2530-35 4036-41 5242-47 3048-53 2154-59 1260-65 666-71 472-77 1

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a. Find the mean, median and modeb. Find the 1st and 3rd quantilec. Find the 4th and 6th deciled. Find the 25th and 75th percentile

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Measure of VariationThe range is considered to be the simplest form

of measure of variation. It is the difference between the highest and the lowest value in the distribution.

R = H – LFor grouped data, the3 difference between the

highest upper class boundary and the lowest lower class boundary.

Example: find the range of the given grouped data in slide no. 59

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Semi-inter Quartile Range

This value is obtained by getting one half of the difference between the third and the first quartile.

Q = (Q3 – Q1)/2

Example: Find the semin-interquartile range of the

previous example in slide no. 59

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Average DeviationThe average deviation refers to the arithmetic

mean of the absolute deviations of the values from the mean of the distribution. This measure is sometimes known as the mean absolute deviation.

AD = Σ│x – x’│/ nWhere x = the individual values x’ = mean of the distribution

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Steps in solving for AD1. Arrange the values in column according to

magnitude2. Compute for the value of the mean x’3. Determine the deviations (x – x’)4. Convert the deviations in step 3 into positive

deviations. Use the absolute value sign.5. Get the sum of the absolute deviations in

step 46. Divide the sum in step 5 by n.

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Example:1. Consider the following values:16, 13, 9, 6, 15, 7, 11, 12Find the average deviation.

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For grouped data:AD = Σf│x – x’│ / nWhere f = frequency of each class x = midpoint of each class x’ = mean of the distribution n = total number of frequency

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Example:Find the average deviation of the given dataClasses f 11-22 223-34 835-46 1147-58 1959-70 1471-82 583-94 1

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VarianceFor ungrouped datas2 = Σ(x – x’)2 / nExample: Find the variance of16, 13, 9, 6, 15, 7, 11, 12

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For grouped datas2 = Σf(x – x’)2 / nWhere f = frequency of each class x = midpoint of each class interval x’ = mean of the distribution n = total number of frequency

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Example: Find the variance of the given dataClasses f 11-22 223-34 835-46 1147-58 1959-70 1471-82 583-94 1

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Coefficient of variationIf you wish to compare the variability between

different sets of scores or data, coefficient of variation would be very useful measure for interval scale data

CV = s/xWhere s = standard deviation x = the mean

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Example:In a particular university, a researcher wishes to

compare the variation in scores of the urban students with that of the scores of the rural students in their college entrance test. It is know that the urban student’s mean score is 384 with a standard deviation of 101; while among the rural students, the mean is 174, with a standard deviation of 53, which group shows more variation in scores?

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Standard Deviation

s = √s2

For ungrouped data s = √ Σ(x – x’)2 / nFor grouped datas = √ Σf(x – x’)2 / n

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Find the standard deviation of the previous examples for ungrouped and grouped data.

Find the standard deviation of the given dataClasses f 11-22 223-34 835-46 1147-58 1959-70 1471-82 583-94 1

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Find the standard deviation of16, 13, 9, 6, 15, 7, 11, 12

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Measure of variation for nominal dataVR = 1 – fm/NWhere VR = the variation ratio fm = modal class frequency N = counting of observation

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Example: With the data given by a clinical psychologist on the

type of therapy used, compute the variation ratios.Type of therapy no. of patients YR 1980 YR 1985Logotherapy 20 8Reality Therapy 60 105Rational Therapy 42 6Transactional analysis 39 9Family therapy 52 5Others 41 8

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Assignment no. 4

I. Compute for the semi-interquartile range, absolute deviation, variance and standard deviation test III of assignment no. 3.

II. Compute for the semi-interquartile range, absolute deviation, variance and standard deviation of test I of assignment no. 3.

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SIMPLE LINEAR REGRESSION AND MEASURES OF CORRELATION

In this topic, you will learn how to predict the value of one dependent variable from the corresponding given value of the independent variable.

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The scatter diagram:In solving problems that concern estimation and

forecasting, a scatter diagram can be used as a graphical approach. This technique consist of joining the points corresponding to the paired scores of dependent and independent variables which are commonly represented by X and Y on the X-Y coordinate system.

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Example:The working experience and income of 8 employees are given

belowEmployee years of income experience (in Thousands) X Y A 2 8 B 8 10 C 4 11 D 11 15 E 5 9 F 13 17 G 4 8 H 15 14

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Using the Least Squares Linear Regression Equation:

Y = a + bXWhere b = [nΣxy – ΣxΣy] / [nΣx2 – (Σx)2] a = y’ – bx’Obtain the equation of the given data and

estimate the income of an employee if the number of years experience is 20 years.

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Standard Error of Estimate Se = √ [ΣYi

2 – a(Yi) – b(XiYi)] / n-2

The standard error of estimate is interpreted as the standard deviation. We will find that the same value of X will always fall between the upper and lower 3Se limits.

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Measures of CorrelationThe degree of relationship between variables is

expressed into:1. Perfect correlation (positive or negative)2. Some degree of correlation (positive or

negative)3. No correlation

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For a perfect correlation, it is either positive or negative represented by +1 and -1. correlation coefficients, positive or negative, is represented by +0.01 to +0.99 and -0.01 to -0.99. The no correlation is represented by 0.

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0 to +0.25 very small positive correlation+0.26 to +0.50 moderately small positive correlation+0.51 to +0.75 high positive correlation+0.76 to +0.99 very high positive correlation+1.00 perfect positive correlation----------------------------------------------------------0 to -0.25 very small negative correlation-0.26 to -0.50 moderately small positive correlation-0.51 to -0.75 high negative correlation-0.76 to -0.99 very high negative correlation-1.00 perfect negative correlation

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Anybody who wants to interpret the results of the coefficient of correlation should be guided by the following reminders:

1. The relationship of two variables does no necessarily mean that one is the cause of the effect of the other variable. It does not imply cause-effect relationship.

2. When the computed Pearson r is high, it does not necessarily mean that one factor is strongly dependent on the other. On the other hand, when the computed Pearson r is small it does not necessarily mean that one factor has no dependence on the other.

3. If there is a reason to believe that the two variables are related and the computed Pearson r is high, these two variables are really meant as associated. On the other hand, if the variables correlated are low, other factors might be responsible for such small association.

4. Lastly, the meaning of correlation coefficient just simply informs us that when two variables change there may be a strong or weak relationship taking place.

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The formula for finding the Pearson r is [nΣXY – ΣXΣY] r = ------------------------------ √[nΣX2 – (ΣX)2] [nΣY2 – (ΣY)2]

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Example: Given two sets of scores. Find the Pearson r and interpret the result.

X Y 18 10 16 14 14 14 13 12 12 10 10 8 10 5 8 6 6 12 3 0

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Correlation between Ordinal DataThis is the Spearman Rank-Order Correlation

Coefficient (Spearman Rho). For cases of 30 or less, Spearman ρ is the most widely used of the rank correlation method.

6ΣD2

ρ = 1 - ----------- n(n2 – 1)Where D = (RX – RY)

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Example:Individual Test X Test Y 1 18 24 2 17 28 3 14 30 4 13 26 5 12 22 6 10 18 7 8 15 8 8 12

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Gamma Rank OrderAn alternative to the rank order correlation is

the Goodman’s and Kruskal’s Gamma (G).The value of one variable can be estimated or

predicted from the other variable when you have the knowledge of their values. The gamma can also be used when ties are found in the ranking of the data.

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NS - N1

G = ----------------- NS + N1

Where NS = the number of pairs ordered in the parallel direction

N1 = the number of pairs ordered in the opposite direction

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Given a segment of the Filipino Electorate according to religion and political party

LAKAS LP NP Total

Catholic 50 25 20

INC 34 72 21

Born Again

22 12 10

Total

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Correlation between Nominal Data

The Guttman’s Coefficient of predictability is the proportionate reduction in error measure which shows the index of how much an error is reduced in predicting values of one variable from the value of another.

ΣFBR - MBC λc = ------------------ N – MBCWhere FBR = the biggest cell frequencies in the ith row MBC = the biggest column totals N = total observations

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ΣFBC - MBR λr = ------------------- N – MBRWhere FBC = the biggest cell frequencies in the

column MBR = the biggest of the row totals N = total number of observationsCompute for the λc and λr for the segment of

Filipino electorate and political parties.

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Assignment no. 51. Given the average yearly cost and sales of company A for a

period of 8 years. Find the pearson r and interpret the results.

Year Cost Sales per P10,000 per P10,0001960 15 381961 30 53.31962 16 601963 39 721964 20 401965 36 47.51966 45 821967 10 21.5

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2. Given the grades of 10 students in statistics determine the spearman rho and interpret the result

Student Q1 Q2 A 62 57 B 90 88 C 75 90 D 60 67 E 58 60 F 89 79 G 91 78 H 90 62 I 94 86 J 50 55

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3. Compute for the gamma shown and interpret the result

Socio-economic status

EDUCATIONAL STATUS TOTAL

UPPER MIDDLE LOWER TOTAL

UPPER 24 19 5

MIDDLE 12 54 29

LOWER 9 26 25

TOTAL

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4. Compute for the λc and λr for the problem no. 3.

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Counting TechniquesConsider the numbers 1,2,3 and 4. suppose you want

to determine the total 2 digit numbers that can be formed if these are combined. First, let us assume that no digit is to be repeated.

12 21 31 4113 23 32 4214 24 34 43Notice that we were able to used all the possibilities. In

this example, we have 12 possible 2 digit numbers.

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Now, what if the digits can be repeated?11 12 13 1421 22 23 2431 23 33 3441 42 43 44Hence, we have 16 possible outcomes.In the first activity, we can do it in n1 ways and after it

has been done, the second activity can be done in n2 ways, then the total number of ways in which the two activities can be done is equal to n1 n2.

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Example:1. How many two digit numbers can be formed from

the numbers 1,2,3 and 4 ifa. Repetition is not allowed?b. Repetition is allowed?2. How many three digit numbers can be formed from

the digits 1,2,3,4 and 5 if any of the digits can be repeated?

3. The club members are going to elect their officers. If there are 5 candidates for president, 5 candidates for vice president and 3 for secretary, then how many ways can the officers be elected?

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4. An office executive plans to buy as laptop in which there are 5 brands available. Each of the brands has 3 models and each model has 5 colors to chose from. In how many ways can the executive choose?

5. Consider the numbers 2,3 5 and 7. if repetition is not allowed, how many three digit numbers can be formed such that

a. They are all odd?b. They are all even?c. They are greater that 500?

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6. A pizza place offers 3 choices of salad, 20 kinds of pizza and 4 different deserts. How many different 3 course meals can one order?

7. The executive of a certain company is consist of 5 males and 2 females. How many ways can the presidents and secretary be chosen if

a. The president must be female and the secretary must be male?

b. The president and the secretary are of opposite sex?

c. The president and the secretary should be male?

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Permutation The term permutation refers to the

arrangement of objects with reference to order.

P(n,r) = n! / (n – r)!Evaluate:1. P(10,6)2. P(5,5)3. P(4,3) + P(4,4)

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Examples:1. In how many ways can a president, a vice

president, a secretary and a treasurer be elected from a class with 40 students?

2. In how many ways can 7 individuals be seated in a row of 7 chairs?

3. In how many ways can 9 individuals be seated in a row of 9 chairs if two individuals wanted to be seated side by side?

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4. Suppose 5 different math books and 7 different physics books shall be arranged in a shelf. In how many ways can such books be arranged if the books of the same subject be placed side by side?

5. Determine the possible permutations of the word MISSISSIPPI.

6. Find the total 8 digit numbers that can be formed using all the digits in the following numerals 55777115

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7. In how many ways can 6 persons be seated around a table with 6 chairs if two individuals wanted to be seated side by side?

8. In a local election, there are 7 people running for 3 positions. In how many ways can this be done?

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Combination A combination is an arrangement of objects not

in particular order.nCr = C(n,r) = n! / r!(n-r)!Evaluate:1. 8C4

2. 5(5C4 – 5C2)

3. 7C5 / (7C6 – 7C2)

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1. A class is consist of 12 boys and 10 girls.a. In how many ways can the class elect the

president, vice president, secretary and a treasurer?

b. In how many ways can the class elect 4 members of a certain committee?

2. In how many ways can a student answer 6 out of ten questions?

3. In how many ways can a student answer 6 out of 10 questions if he is required to answer 2 of the first 5 questions?

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4. In how many ways can 3 balls be drawn from a box containing 8 red and 6 green balls?

5. A box contain 8 red and 6 green balls. In how many ways can 3 balls be drawn such that

a. They are all green?b. 2 is red and 1 is green?c. 1 is red and 2 is green?

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6. A shipment of 40 computers are unloaded from the van and tested. 6 of them are defective. In how many ways can we select a set of 5 computers and get at least one defective?

7. Five letters a,b,c,d,e are to be chosen. In how many ways could you choose

a. None of themb. At least two of themc. At most three of them

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Assignment no. 61. How many possible outcomes are there ifa. A die is rolled?b. A pair of dice is rolled?2. In how many ways can 5 math teachers be

assigned to 4 available subjects if each of the 5 teachers have equal chance of being assigned to any of the 4 subjects?

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3. Consider the numbers 1,2,3,5,and 6. how many 3 digit numbers can be formed from these numbers if

a. Repetition is not allowed and 0 should not be in the first digit?

b. Repetition is allowed and 0 should not be in the first digit?

4. A college has 3 entrance gates and 2 exit gates. In how many ways can a student enter then leave the building?

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5. In how many ways can 9 passengers be seated in a bus if there are only 5 seats available?

6. In how many ways can 4 boys and 4 girls be seated in a row of 8 chairs if

a. They can sit anywhere?b. The boys and girls are to be seated

alternately?7. In how many ways can ten participants in a

race placed first, second and third?

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8. Determine the number of distinct permutations of each of the following:

a. STATISTICSb. ADRENALINc. 440449994049. A class consist of 12 boys and 10 girls. In

how many ways can a committee of five be formed if

a. All members are boys?b. 2 are boys and 3 are girls?

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10. In how many ways can a student answer an exam if out of the 6 problem, he is required to answer only 4?