30
EdPsy 511 August 28, 2007

EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

  • View
    219

  • Download
    3

Embed Size (px)

Citation preview

Page 1: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

EdPsy 511

August 28, 2007

Page 2: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Common Research Designs

• Correlational– Do two qualities “go together”.

• Comparing intact groups– a.k.a. causal-comparative and ex post facto designs.

• Quasi-experiments– Researcher manipulates IV

• True experiments– Must have random assignment.

• Why?

– Researcher manipulates IV

Page 3: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Measurement

• Is the assignment of numerals to objects.– Nominal

• Examples: Gender, party affiliation, and place of birth

• Ordinal– Examples: SES, Student rank, and Place in race

• Interval– Examples: Test scores, personality and attitude scales.

• Ratio– Examples: Weight, length, reaction time, and number of

responses

Page 4: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Categorical, Continuous and Discontinuous

• Categorical (nominal)– Gender, party affiliation, etc.

• Discontinuous– No intermediate values

• Children, deaths, accidents, etc.

• Continuous– Variable may assume an value

• Age, weight, blood sugar, etc.

Page 5: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Values

• Exhaustive– Must be able to assign a value to all objects.

• Mutually Exclusive– Each object can only be assigned one of a set

of values.

• A variable with only one value is not a variable.– It is a constant.

Page 6: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Chapter 2: Statistical Notation• Nouns, Adjectives, Verbs and

Adverbs.– Say what?

• Here’s what you need to know– X

• Xi = a specific observation– N

• # of observations– ∑

• Sigma– Means to sum

– Work from left to right• Perform operations in

parentheses first• Exponentiation and square

roots• Perform summing operations• Simplify numerator and divisor• Multiplication and division• Addition and subtraction

N

iiX

1

Page 7: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

• Pop Quiz (non graded)– In groups of three or four

• Perform the indicated operations.

• What was that?

1

)( 22

2

nn

XX

s

Page 8: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Rounding Numbers

• Textbook describes a somewhat complex rounding rule.– For this class, truncate at the thousandths

place.• e.g. 3.45678 3.456

Page 9: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Chapter 3

Exploratory Data Analysis

Page 10: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Exploratory Data Analysis

• A set of tools to help us exam data– Visually representing data makes it easy to

see patterns.• 49, 10, 8, 26, 16, 18, 47, 41, 45, 36, 12, 42, 46, 6,

4, 23, 2, 43, 35, 32

– Can you see a pattern in the above data?• Imagine if the data set was larger.

– 100 cases– 1000 cases

Page 11: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Three goals

• Central tendency– What is the most common score?– What number best represents the data?

• Dispersion– What is the spread of the scores?

• What is the shape of the distribution?

Page 12: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Frequency Tables

• Let say a teacher gives her students a spelling test and wants to understand the distribution of the resultant scores.– 5, 4, 6, 3, 5, 7, 2, 4, 3, 4

Value F Cumulative F % Cum%

7 1 1 10% 10%

6 1 2 10% 20%

5 2 4 20% 40%

4 3 7 30% 70%

3 2 9 20% 90%

2 1 10 10% 100%

N=10

Page 13: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

As groups

• Create a frequency table using the following values.– 20, 20, 17, 17, 17, 16, 14, 11, 11, 9

Page 14: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

As groups

• Create a frequency table using the following values.– 20, 19, 17, 16, 15, 14, 12, 11, 10, 9

Page 15: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Banded Intervals

• A.k.a. Grouped frequency tables

• With the previous data the frequency table did not help.– Why?

• Solution: Create intervals

• Try building a table using the following intervals<=13, 14 – 18, 19+

Page 16: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Stem-and-leaf plots

• Babe Ruth– Hit the following number of Home Runs from 1920 –

1934.• 54, 59, 35, 41, 46, 25, 47, 60, 54, 46, 49, 46, 41, 34, 22

– As a group let’ build a stem and leaf plot

– With two classes’ spelling scores on a 50 item test.

• Class 1: 49, 46, 42, 38, 34, 33, 32, 30, 29, 25 • Class 2: 39, 38, 38, 36, 36, 31, 29, 29, 28, 19

– As a group let’ build a stem and leaf plot

Page 17: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Landmarks in the data

• Quartiles– We’re often interested in the 25th, 50th and 75th

percentiles.• 39, 38, 38, 36, 36, 31, 29, 29, 28, 19

– Steps• First, order the scores from least to greatest.• Second, Add 1 to the sample size.

– Why?• Third, Multiply sample size by percentile to find location.

– Q1 = (10 + 1) * .25– Q2 = (10 + 1) * .50– Q3 = (10 + 1) * .75

» If the value obtained is a fraction take the average of the two adjacent X values.

Page 18: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Box-and-Whiskers Plots (a.k.a., Boxplots)

Page 19: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Shapes of Distributions

• Normal distribution

• Positive Skew– Or right skewed

• Negative Skew– Or left skewed

Page 20: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

How is this variable distributed?

87654321

score

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Frequency

Mean = 4.3Std. Dev. = 1.494N = 10

Page 21: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

How is this variable distributed?

7.006.005.004.003.002.001.000.00

right

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Frequency

Mean = 2.80Std. Dev. = 1.75119N = 10

Page 22: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

How is this variable distributed?

8.007.006.005.004.003.002.00

left

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Frequency

Mean = 5.40Std. Dev. = 1.42984N = 10

Page 23: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Descriptive Statistics

Page 24: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Statistics vs. Parameters

• A parameter is a characteristic of a population.– It is a numerical or graphic way to summarize data

obtained from the population

• A statistic is a characteristic of a sample.– It is a numerical or graphic way to summarize data

obtained from a sample

Page 25: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Types of Numerical Data

• There are two fundamental types of numerical data:

1) Categorical data: obtained by determining the frequency of occurrences in each of several categories

2) Quantitative data: obtained by determining placement on a scale that indicates amount or degree

Page 26: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Measures of Central Tendency

Central Tendency

Average (Mean) Median Mode

1

1

n

ii

N

ii

XX

n

X

N

Page 27: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Mean (Arithmetic Mean)

• Mean (arithmetic mean) of data values– Sample mean

– Population mean

1 1 2

n

ii n

XX X X

Xn n

1 1 2

N

ii N

XX X X

N N

Sample Size

Population Size

Page 28: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Mean

• The most common measure of central tendency

• Affected by extreme values (outliers)

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

Page 29: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Median

• Robust measure of central tendency• Not affected by extreme values

• In an Ordered array, median is the “middle” number– If n or N is odd, median is the middle number– If n or N is even, median is the average of the two

middle numbers

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 Median = 5

Page 30: EdPsy 511 August 28, 2007. Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and

Mode• A measure of central tendency• Value that occurs most often• Not affected by extreme values• Used for either numerical or categorical data• There may may be no mode• There may be several modes

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