# 13. Statistics, Tests and Measurements (Ch2)

### 13.1 Descriptive and Inferential Statistics Samples, populations, norms

- Statistics
- collection, analysis, interpretation, and presentation of numeric data

- Samples
- representative subset of larger population
- random sample

- Populations
- group of people looking to study

- Norms
- identifying normal behavior of group to compare to
- standardizing

- Descriptive Statistics
- used for correlational and experimental designs
- measurements of behavior from sample

- Mean
- average

- Mode
- most commonly occurring score

- Median
- middle score, separates lower and upper halves of scores

- Standard Deviation
- statistical measure of how much scores in a sample vary around the mean
- higher SD = more variability (more spread)
- lower SD = less variability (less spread)

- Normal Distribution
- bell curve showing symmetrical alignment of two variables (e.g Intelligence)

- Inferential Statistics
- inferences about population based on characteristics of sample

- statistical significance
- not likely to have happened by chance
- significant equals 5% of the time or less

### 13.2 Reliability and Validity

Reliability

- stability and consistency of scores
- does not need to be valid to be reliable

Types of Reliability

- test-retest reliability

- internal consistency
- How well does a test correlate with itself

- split-half reliability
- Cronbach’s alpha: avg correlation for every way a test can be split in half

Validity

- how well a test measures what it is supposed to measure
- must be reliable to be valid

Types of validity

- face/content validity
- whether a test looks as though it is measuring what it is supposed to measure

- predictive validity
- how well scores on the test predict the actual behavior of the type that the test is supposed to measure

- construct validity
- whether the scores on a questionnaire are related in expected ways, either positively or negatively, to scores on other questionnaires that are proposing to measure the same thing.

- face/content validity
standardizing measures

### 13.3 Types of Tests

- Tests used to rule out chance
- t-test: computed for two means to see if they come from same population (e.g., of two groups or variables)
- ANOVA: analysis of variance

- Pearson correlation coefficient (-1.0 to +1.0)

### 13.4 Measurement of Intelligence

Stanford-Binet Intelligence Scale

- first IQ test
- still widely used today
- norming and standardization

Wechsler Intelligence Tests

- WAIS- IV: Adult
- WISC-V: Children
- WPPSI-IV: Pre-school and primary school

Flynn effect

- each generation, higher IQ

### Quiz

- Which of the following is a measure of central tendency that can be easily distorted by unusually high or low scores?
**(A) Mean**- (B) Mode
- (C) Median
- (D) Range
- (E) Standard deviation

- Which of the following statistics indicates the distribution with the greatest variability?
- A variance of 30.6
**(B) A standard deviation of 11.2**- (C) A range of 6
- (D) A mean of 61.5
- (E) A median of 38

- Which of the following is a true statement about the relationship between test validity and test reliability?
**(A) A test can be reliable without being valid.**- (B) A test that has high content validity will have high reliability.
- (C) A test that has low content validity will have low reliability.
- (D) The higher the test’s validity, the lower its reliability will be.
- (E) The validity of a test always exceeds its reliability.

- If the null hypothesis is rejected, a researcher can conclude that the
**(A) treatment effect was significant**- (B) theory must be modified, a new hypothesis formed, and the experimental procedure revised
- (C) theory does not need modification, but the hypothesis and the experimental procedure need revision
- (D) theory and hypothesis do not need modification, but the experimental procedure needs revision
- (E) hypothesis is false

- In order to illustrate how often a particular score occurs in a given data set, researchers use
- (A) inferential techniques
- (B) cognitive mapping
- (C) cluster analysis
- (D) the median
**(E) a frequency distribution**