Psych Assessment Norms and Statistics for Testing.pptx

Psych Assessment Norms and Statistics for Testing

1. Norms and Basic Statistics for Testing Psychological Testing and Assessment

2. Why We Need Statistics

3. Why We Need Statistics Data gathering and analysis might be considered analogous to criminal investigation and prosecution (Cox, 2006; Regenwetter , 2006; Tukey) First comes the detective work of gathering and displaying clues, or what the statistician John Tukey calls exploratory data analysis . Then comes a period of confirmatory data analysis , when the clues are evaluated against rigid statistical rules.  Descriptive statistics are methods used to provide a concise description of a collection of quantitative information. Inferential statistics are methods used to make inferences from observations of a small group of people known as a sample to a larger group of individuals known as a population. 

4. Scales of Measurement

5. Properties of Scales

6. NOMINAL: -Eye Color (e.g. Blue, Brown, Green) -Nationality (e.g. German, Filipino, Lebanese) -Personality Type (e.g. Introvert, Extrovert) -Employment Status (e.g. Unemployed, Part-time, Retired) -Type of Smartphone Owned (e.g. Iphone , Samsung, Google Pixel)

7. ORDINAL -Academic Grades (A, B, C…) -Satisfaction (Extremely Satisfied, Quite Satisfied, Slightly Dissatisfied, Extremely Dissatisfied) -Level Of Education Completed (High School, Bachelor’s Degree, Master’s Degree) -Seniority Level At Work (Junior, Mid-level, Senior)

8. INTERVAL - Temperature In Degrees Fahrenheit or Celsius (But not Kelvin) -IQ Score -Income Categorized as Ranges (P30-39k, P40-49k, P50-59k, and so on)

9. RATIO -Weight in grams -Number of employees at a company -Speed in miles per hour -Length in centimeters -Age in years -Income in dollars

10. Frequency Distributions The frequency distribution displays scores on a variable or a measure to reflect how frequently each value was obtained. 

11. Percentile ranks Percentile ranks replace simple ranks when we want to adjust for the number of scores in a group. A percentile rank answers the question, “What percent of the scores fall below a particular score (Xi)?”

12. Percentiles Percentiles are the specific scores or points within a distribution. Percentiles divide the total frequency for a set of observations into hundredths. Instead of indicating what percentage of scores fall below a particular score, as percentile ranks do, percentiles indicate the particular score, below which a defined percentage of scores falls.

13. PERCENTILE rank VS PERCENTILE Percentile Rank: This is a percentage indicating how a particular value (like a test score) compares to the rest of the scores in a distribution. For example, a percentile rank of 80 means that 80% of the scores in the distribution are lower than that specific score.  Percentile: This is a value itself that divides a dataset into 100 equal parts. The nth percentile represents the value below which n% of the data points fall. For example, the 75th percentile is the value that separates the bottom 75% of the data from the top 25%.  Example:  Imagine a class of 100 students took a test.  If Sarah scores at the 80th percentile, it means that 80% of the students scored below her. Her percentile rank is 80.  If the 75th percentile score was 85, it means that 75% of the students scored 85 or less. 85 is the value at the 75th percentile. 

14. DESCRIBING DATA

15. MEASURES OF CENTRAL TENDENCY 1. MEAN The arithmetic average score in a distribution is called the mean. To calculate the mean, we total the scores and divide the sum by the number of cases, or N. The capital Greek letter sigma (S) means summation.

16. MEASURES OF CENTRAL TENDENCY 2. MEDIAN The median, defined as the middle score in a distribution, is determined by ordering the scores in a list by magnitude, in either ascending or descending order. To calculate the median, first arrange the data set in ascending order. If the number of data points is odd, the median is the middle value. If the number of data points is even, the median is the average of the two middle values.  Example: Data set: 2, 5, 1, 8, 4  Arrange in ascending order: 1, 2, 4, 5, 8  The median is the middle value, which is 4. 

17. MEASURES OF CENTRAL TENDENCY 3. MODE The most frequently occurring score in a distribution of scores is the mode. As an example, determine the mode for the following scores obtained by another TRW job applicant, Bruce. The scores reflect the number of words Bruce word-processed in seven 1-minute trials: 43 34 45 51 42 31 51

18. MEASURES OF VARIABILITY Variability is an indication of how scores in a distribution are scattered or dispersed. 1. The range of a distribution is equal to the difference between the highest and the lowest scores. 2. A distribution of test scores can be divided into four parts are quartiles .  3. T he interquartile range is a measure of variability equal to the difference between Q3 and Q1.

19. SKEWNESS Skewness is an indication of how the measurements in a distribution are distributed. A distribution has a positive skew when relatively few of the scores fall at the high end of the distribution. A distribution has a negative skew when relatively few of the scores fall at the low end of the distribution.

20. Describing Distributions STANDARD DEVIATION The standard deviation is an approximation of the average deviation around the mean.

21. NORMS Norms refer to the performances by defined groups on particular tests.  Age-Related Norms- Certain tests have different normative groups for particular age groups. A norm-referenced test compares each person with a norm. A criterion-referenced test describes the specific types of skills, tasks, or knowledge that the test taker can demonstrate such as mathematical skills