Click here to load reader
Upload
olaf
View
176
Download
29
Tags:
Embed Size (px)
DESCRIPTION
STATISTICAL TOOLS NEEDED IN ANALYZING TEST RESULTS Prof. Yonardo Agustin Gabuyo. Statistics is a branch of science which deals with the collection, presentation, analysis and interpretation of quantitative data. Branches of Statistics. Descriptive statistics - PowerPoint PPT Presentation
Citation preview
STATISTICAL TOOLSNEEDED
IN ANALYZING TEST RESULTS
Prof. Yonardo Agustin Gabuyo
Branches of StatisticsDescriptive statistics methods concerned w/ collecting, describing, and analyzing a set of data without drawing conclusions (or inferences) about a large group
Inferential statistics methods concerned with the analysis of a subset of data leading to predictions or inferences about the entire set of data or population.
Examples of Descriptive Statistics Presenting the Philippine population by constructing a graph indicating the total number of Filipinos counted during the last census by age group and sex
The Department of Social Welfare and Development (DSWD) cited statistics showing an increase in the number of child abuse cases during the past five years.
Examples of Inferential Statistics Source: Pilot Training Course on Teaching Basic Statistics by Statistical Research and Training Center Philippine Statistical
Association , Inc.
A new milk formulation designed to improve the psychomotor development of infants was tested on randomly selected infants. Based on the results, it was concluded that the new milk formulation is effective in improving the psychomotor development of infants.
Example
Teacher Ron-nick gave a personality test measuring shyness to 25,000 students. What is the average degree of shyness and what is the degree to which the students differ in shyness are the concerns of _________ statistics.
A. inferential B. graphic
C. correlational D. descriptive
ExampleThis is a type of statistics that give/s information about the sample being studied.
a. Inferential and co-relationalb. Inferentialc. Descriptived. Co relational
Inferential StatisticsSource: Pilot Training Course on Teaching Basic Statistics by Statistical Research and Training Center Philippine Statistical Association , Inc.
Larger Set(N units/observations) Smaller Set
(n units/observations)
Inferences and Generalizations
VARIABLES
Qualitative Quantitative
ContinuousDiscrete
Types of Variables
Qualitative variables variables that can be express in terms of properties, characteristics, or classification(non-numerical values).
Levels of Measurement1. Nominal
Numbers or symbols used to classify
2. Ordinal scale Accounts for order; no indication
of distance between positions3. Interval scale
Equal intervals; no absolute zero4. Ratio scale
Has absolute zero
Methods of Collecting Data Objective Method
Subjective Method
Use of Existing Records
Methods of Presenting Data Textual
Tabular
Graphical
Mean
Median
Mode
Summary Measures
Variation
Variance
Standard Deviation
Coefficient of Variation
Range
Location
Maximum Minimum
Central Tendency
Percentile
Quartile Decile
Inter-quartile Range
Skewness
Kurtosis
Measures of Location
A Measure of Location summarizes a data set by giving a “typical value” within the range of the data values that describes its location relative to entire data set.Some Common Measures:Minimum, MaximumCentral TendencyPercentiles, Deciles, Quartiles
Maximum and Minimum Minimum is the smallest value in the
data set, denoted as MIN.
Maximum is the largest value in the data set, denoted as MAX.
Measure of Central Tendency A single value that is used to identify the “center” of the data it is thought of as a typical value of the distribution
precise yet simplemost representative value of the data
Mean Most common measure of the center Also known as arithmetic average
Sample Mean
Population Mean
Properties of the Mean may not be an actual
observation in the data set. can be applied in at least
interval level. easy to compute. every observation
contributes to the value of the mean.
Properties of the Mean subgroup means can be
combined to come up with a group mean
easily affected by extreme values
0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 12 14
Mean = 5 Mean = 6
Median Divides the observations into two
equal parts. If n is odd, the median is the
middle number. If n is even, the median is the
average of the 2 middle numbers. Sample median denoted as
while population median is denoted as
x~ ~
Properties of a Median may not be an actual observation in
the data set can be applied in at least ordinal level a positional measure; not affected by
extreme values
0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 12 14
Median = 5
Mode the score/s that occurs most
frequently nominal average computation of the mode for
ungrouped or raw data
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Mode = 9
0 1 2 3 4 5 6
No Mode
Properties of a Mode can be used for qualitative as
well as quantitative data may not be unique not affected by extreme values may not exist
Mean, Median & ModeUse the mean when:
sampling stability is desired other measures are to be
computed
Mean, Median & Mode
Use the median when:
the exact midpoint of the distribution is desired
there are extreme observations
Mean, Median & Mode
Use the mode when:
when the "typical" value is desired
when the dataset is measured on a nominal scale
Example
Which measure(s) of central tendency is(are) most appropriate when the score distribution is skewed?
A. ModeB. Mean and modeC. Median D. Mean
Example
In one hundred-item test, what does Jay-R’s score of 70 mean?
A. He surpassed 70 of his classmate in terms of score
B. He surpassed 30 of his classmates in terms of score
C. He got a score above meanD. He got 70 items correct
Example
Which of the following measures is more affected by an extreme score?
A. Semi- inter quartile rangeB. Median C. Mode D. Mean
Example
The sum of all the scores in a distribution always equals
a. The mean times the interval size
b. The mean divided by the interval size
c. The mean times Nd. The mean divided by N
Example
Teacher B is researching on family income distribution which is symmetrical. Which measure/s of central tendency will be most informative and appropriate?
A. ModeB. MeanC. MedianD. Mean and Median
Example
What measure/s of central tendency does the number 16 represent in the following score distribution? 14,15,17,16,19,20,16,14,16?
a.Mode onlyb.Mode and medianc. Median onlyd. Mean and mode
Example
What is the mean of this score distribution: 40, 42, 45, 48, 50, 52, 54, 68?
a. 51.88b. 50.88c. 49.88d. 68
Example
Which is the correct about MEDIAN?
a. It is measure of variabilityb. It is the most stable measure of central tendency
c. It is the 50th percentiled. It is significantly affected by extreme values
Example
Which measure(s) of central tendency can be determined by mere inspection?
a. Medianb. Modec. Meand. Mode and Median
Example
Here is a score distribution: 98,93,93,93,90,88,88,85,85,85,86, 70,70,51,34,34,34,, 20,18,15,12,9,8,3,1.
Which is a characteristics of the scores distribution?
A. Bi-modal B. Tri-modalC. Skewed to the right D. No discernible pattern
Example
Which is true of a bimodal score distribution?
a. the group tested has two identical scores that appeared most.
b. the scores are either high or low.
c. the scores are high.d. the scores are low.
ExampleSTUDY THE TABLE THEN ANSWER THE
QUESTION:
Scores Percent of Students
0-59 2%60-69 8%70-79 39%80-89 38%90-100 13%
In which scores interval is the median?
a. In the interval 80 to 89b. In between the intervals of 60-69 and 70-79
c. In the interval 70-79d. In the interval 60-69
How many percent of the students got a score below 70?
a. 2%b. 8%c. 10%d. 39%
Percentiles Numerical measures that
give the relative position of a data value relative to the entire data set.
Percentage of the students in the reference group who fall below student’s raw score.
Divides the scores in the distribution into 100 equal parts (raw data arranged in increasing or decreasing order of magnitude).
The jth percentile, denoted as Pj, is the data value in the data set that separates the bottom j% of the data from the top (100-j)%.
EXAMPLESuppose JM was told that relative to the other scores on a certain test, his score was the 97th percentile. This means that 97% of those who took the test had scores less than JM’s score, while 3% had scores higher than JM’s.
DecilesDivides the scores in the
distribution into ten equal parts, each part having ten percent of the distribution of the data values below the indicated decile.
The 1st decile is the 10th percentile; the 2nd decile is the 20th percentile…..
9th decile is the 90th percentile.
Quartiles Divides the scores in the distribution
into four equal parts, each part having 25% of the scores in the distribution of the data values below the indicated quartile.
The 1st quartile is the 25th percentile; the 2nd quartile is the 50th percentile, also the median and the 3rd quartile is the 75th percentile.
Example
Robert Joseph’s raw score in the mathematics class is 45 which equal to 96th percentile. What does this mean?
a. 96% of Robert Joseph’s classmates got a score higher than 45.
b. 96% of Robert Joseph’s classmates got a score lower than 45.
c. Robert Joseph’s score is less than 45% of his classmates.
d. Roberts Joseph’s is higher than 96% of his classmates.
Example
Which one describes the percentile rank of a given score?
a. The percent of cases of a distribution below and above a given score.
b. The percent of cases of a distribution below the given score.
c. The percent of cases of a distribution above the given score.
d. The percent of cases of a distribution within the given score.
Example
Biboy obtained a score of 85 in Mathematics multiple choice tests. What does this mean?
a. He has a rating of 85
b. He answered 85 items in the test correctly
c. He answered 85% of the test item correctly
d. His performance is 15% better than the group
Example
Median is the 50th percentile as Q3 is to
a. 45th percentileb. 70th percentilec. 75th percentiled. 25th percentile
Example
Karl Vince obtained a NEAT percentile rank of 95. This means that
a. They have a zero reference pointb. They have scales of equal unitsc. They indicate an individual’s relative standing in a group
d. They indicate specific points in the normal curve
Example
Markie obtained a NEAT percentile rank of 95.
This means thata. He got a score of 95.b. He answered 95 items correctly.
c. He surpassed in performance of 95% of his fellow examinees.
d. He surpassed in performance 0f 5% of his fellow examinees.
Example
What is/are important to state when explaining percentile-ranked tests to parents?
I. What group took the testII. That the scores show how students
performed in relation to other studentsIII. That the scores show how students
performed in relation to an absolute measure
A. II only B. I & IIIC. I & II D. III only
Measures of VariationA measure of variation is a single value that is used to describe the spread of the distribution.
A measure of central tendency alone does not uniquely describe a distribution.
Mean = 15.5 s = 3.338
11 12 13 14 15 16 17 18 19 20 21
11 12 13 14 15 16 17 18 19 20 21
Section B
Section A
Mean = 15.5
s = .9258
11 12 13 14 15 16 17 18 19 20 21
Mean = 15.5 s = 4.57
Section C
A look at dispersion… Pilot Source: Training Course on Teaching Basic Statistics by Statistical Research and Training Center Philippine Statistical Association , Inc.
Two Types of Measures of Dispersion
Absolute Measures of Dispersion: Range Inter-quartile Range Variance Standard Deviation
Relative Measure of Dispersion: Coefficient of Variation
Range (R)The difference between the maximum and minimum value in a data set, i.e.
R = MAX – MINExample: Scores of 15 students in mathematics quiz. 54 58 58 60 62 65 66 71 74 75 77 78 80 82 85
R = 85 - 54 = 31
Some Properties of the Range The larger the value of the
range, the more dispersed the observations are.
It is quick and easy to understand.
A rough measure of dispersion.
Inter-Quartile Range (IQR)The difference between the third quartile and first quartile, i.e.
IQR = Q3 – Q1
Example: Scores of 15 students in mathematics quiz.
54 58 58 60 62 65 66 71 74 75 77 79 82 82 85
IQR = 78 - 61 = 17
Some Properties of IQR Reduces the influence of
extreme values.
Not as easy to calculate as the Range.
Consider only the middle 50% of the scores in the distribution
Quartile deviation (QD)is based on the range of the middle 50% of the scores, instead of the range of the entire set.
it indicates the distance we need to go above and below the median to include approximately the middle 50% of the scores.
Variance important measure of variation
shows variation about the mean
Population variance
Sample variance
Standard Deviation (SD) most important measure of variation
square root of Variancehas the same units as the original data
is the average of the degree to which a set of scores deviate from the mean value
it is the most stable measures of variability
Population SD
Sample SD
Data: 10 12 14 15 17 18 18 24 are the scores of students in mathematics quiz.
n = 8 Mean =16
309.4 7
2)1624(2)1618()1618(2)1617(2)1615(2)1614(2)1612(2)1610( 2
s
Computation of Standard Deviation
Remarks on Standard Deviation
If there is a large amount of variation, then on average, the data values will be far from the mean. Hence, the SD will be large.
If there is only a small amount of variation, then on average, the data values will be close to the mean. Hence, the SD will be small.
Mean = 15.5 s = 3.338 11 12 13 14 15 16 17 18 19 20 21
11 12 13 14 15 16 17 18 19 20 21
Section B
Section A
Mean = 15.5 s = .9258
11 12 13 14 15 16 17 18 19 20 21
Mean = 15.5 s = 4.57
Section C
Comparing Standard Deviation
Example: Team A - Heights of five marathon players in inches
65”
65 “ 65 “ 65 “ 65 “ 65 “
Mean = 65 S = 0
Comparing Standard Deviation
Example: Team B - Heights of five marathon players in inches
62 “ 67 “ 66 “ 70 “ 60 “
Mean = 65” s = 4.0”
Comparing Standard Deviation
Properties of Standard Deviation It is the most widely used measure of dispersion. (Chebychev’s Inequality)
It is based on all the items and is rigidly defined.
It is used to test the reliability of measures calculated from samples.
The standard deviation is sensitive to the presence of extreme values.
It is not easy to calculate by hand (unlike the range).
Chebyshev’s Rule
It permits us to make statements about the percentage of observations that must be within a specified number of standard deviation from the mean
The proportion of any distribution that lies within k standard deviations of the mean is at least 1-(1/k2) where k is any positive number larger than 1.
This rule applies to any distribution.
Chebyshev’s Rule For any data set with mean () and standard deviation (SD), the following statements apply:
At least 75% of the observations are within 2SD of its mean.
At least 88.9% of the observations are within 3SD of its mean.
Illustration
At least 75%
At least 75% of the observations are within 2SD of its mean.
ExampleThe pre-test scores of the 125 LET reviewees last year had a mean of 70 and a standard deviation of 7 points.
Applying the Chebyshev’s Rule, we can say that:
1. At least 75% of the students had scores between 56 and 84.
2. At least 88.9% of the students had scores between 49 and 91.
Coefficient of Variation (CV)
measure of relative variation usually expressed in percent shows variation relative to mean used to compare 2 or more groups
Formula : 100%
Mean
SDCV
Comparing CVsGroup A: Average Score = 90
SD = 15 CV = 16.67%
Group B: Average Score = 92 SD = 10 CV = 10.86%
Example
Mark Erick is one-half standard deviation above the mean of his group in math and one standard deviation above English. What does this imply?
a. He excels in both English and Math.
b. He is better in Math than English.c. He does not excel in English nor in Math.
d. He is better is English than Math.
Example
Which statement about the standard deviation is CORRECT?
a. The lower the standard deviation the more spread the scores are.
b. The higher the standard deviation the less the scores spread
c. The higher the standard deviation the more the spread the scores are
d. It is a measure of central tendency
Example
Which group of scores is most varied? The group with________.
a.sd = 9b.sd = 5c.sd = 1d.sd = 7
Example
Mean is to Measure of Central Tendency as___________ is to measure of variability.
a. Quartile Deviationb. Quartilec. Correlationd. Skewness
ExampleHERE ARE TWO SETS OF SCORES: SET A : 1,2,3,4,5,6,7,8,9
SET B : 3,4,4,5,5,6,6,7,9Which statement correctly applies to the twosets of score distribution?a. The scores in Set A are more spread out than
those in set B.b. The range for Set B is 5.c. The range for Set A is 8.d. The scores in Set B are more spread out
than those in Set A.
Measure of Skewness
Describes the degree of departures of the distribution of the data from symmetry.
The degree of skewness is measured by the coefficient of skewness, denoted as SK and computed as,
SD
MedianMeanK
3S
What is Symmetry?
A distribution is said to be symmetric about the mean, if the distribution to the left of mean is the “mirror image” of the distribution to the right of the mean. Likewise, a symmetric distribution has SK=0 since its mean is equal to its median and its mode.
Measure of Skewness
SK > 0positively skewed
SK < 0negatively skewed
Areas Under the Normal Curve
Correlationrefers to the extent to which the distributions are related or associated.
the extent of correlation is indicated by the numerically by the coefficient of correlation.
the coefficient of correlation ranges from -1 to +1.
Types of Correlation1.Positive Correlationa)High scores in distribution A are associated with high scores in distribution B.
b)Low scores in distribution A are associated with low scores in distribution B.
2. Negative Correlationa)High scores in distribution A
are associated with low scores in distribution B.
b)Low scores in distribution A are associated with high scores in distribution B.
3. Zero Correlationa) No association between distribution
A and distribution B. No discernable pattern.
Positive CorrelationScience Score
Math Score
Negative CorrelationScience Score
Math Score
No CorrelationScience
Math
Example
Skewed score distribution means:a. The scores are normally distributed.
b. The mean and the median are equal.
c. Consist of academically poor students.
d. The scores are concentrated more at one end or the other end
Example
Skewed score distribution means:a. The scores are normally distributed.
b. The mean and the median are equal.
c. Consist of academically poor students.
d. The scores are concentrated more at one end or the other end
Example
What would be most likely most the distribution if a class is composed of bright students?
a. platykurtic b. skewed to the right c. skewed to the left d. very normal
Example
All the students who took the examination, got
scores above the mean. What is the graphical
representation of the score distribution?
a. normal curveb. mesokurticc. positively skewedd. negatively skewed
A class is composed of academically poor students. The distribution most likely to be______________.
a. skewed to the rightb. a bell curvec. leptokurticd. skewed to the left
Z-SCORE
In statistics, a standard score (also called z-score) is a dimensionless quantity derived by subtracting the population mean from an individual (raw) score and then dividing the difference by the population standard deviation.
The Z-score reveals how many units of the standard deviation a case is above or below the mean. The z-score allows us to compare the results of different normal distributions, something done frequently in research.
whereX is a raw score to be standardizedσ is the standard deviation of the
populationµ is the mean of the population
The quantity z represents the distance between the raw score and the population mean in units of the standard deviation. z is negative when the raw score is below the mean, positive when above.
The Standard score is :
A key point is that calculating z requires the population mean and the population standard deviation, not the sample mean or sample deviation. It requires knowing the population parameters, not the statistics of a sample drawn from the population of interest.N) T-SCORE
it is equivalent to ten times the Z-score plus fifty
T=10Z + 50
EXAMPLE: Based on the table shown, who performed better, JR or JM? Assume a normal distribution.
Student Raw Score Mean Standard DeviationJR 75 65 4JM 58 52 2
For JR
For JM
JM performed better than JR due to a greater value of z.
From the previous example, the T-score of JR is
T JR = 10(2.5) + 50 = 75
While the T-score of JM is
T JM = 10(3) + 50 = 80Therefore, JM performed better than JR due to higher T-score
O) STANINEStanine (Standard NINE)
Is a method of scaling test scores on a nine-point standard scale in a normal distribution.
Percentage Distribution
4% 7% 12% 17% 20% 17% 12% 7% 4%
Cumulative Percentage Distribution
4% 11% 23% 40% 60% 77% 89% 96% 100%
STANINE 1 2 3 4 5 6 7 8 9
ExampleStudy this group of test which was administered to a class to whom Jar-R belongs, then answer the question:
Subject Mean SD Jay-R’s Score
Math 56 10 43Physics 55 9.5 51English 80 11.25
88PE 75 9.75 82
In which subject (s) did Jay-R perform most poorly in relation to the group’s mean performance?
A. EnglishB. PhysicsC. PE D. Math
Based on the data given , what type of learner is Jay-R?
A. LogicalB. SpatialC. LinguisticD. Bodily-Kinesthetic
Based on the data given , in which subject (s) were scores most widespread?
A. MathB. PhysicsC. PED. English
ReferencesPilot Training Course on Teaching Basic
Statistics by Statistical Research and Training Center Philippine Statistical Association , Inc. (Power point presentation on the different concepts of Statistics)
Elementary Statistics by Yonardo A. Gabuyo et. al. Rex Book Store
Assessment of Learning I and II by Dr. Rosita De Guzman-Santos, LORIMAR Publishing, 2007 Ed.
Measurement and Evaluation Concepts and Principles by Abubakar S. Asaad and Wilham M. Hailaya, Rex Book Store
LET Reviewer by Yonardo A. Gabuyo, MET Review Center