1. Four Basic Types Of Measurement:
Categorizing
Nominal
Ranking
Ordinal
Determination of the size interval
Interval
Determination of the size of ratios
Ratio

2. CENTRAL TENDENCY AND VARIABILITY (NOMINAL SCALES)
Information: guessing game (ESP experiments)
Background:
- Transmission of signals
- How much is lost in channel?
- How to measure the information transmitted in a message?

3. CENTRAL TENDENCY AND VARIABILITY (NOMINAL SCALES)
One word - no guesses
Two words - one guess
Four words - two guesses
Eight words - three guesses
-# of guesses - power to which two needs to be raised to define # of words, or log to base 2 of # of alternatives
-Number of guesses called # of bits (binary units)

4. Varying amounts of information

5. Nominal scales:
Name of category does not imply rank, even if it is a number.

6. Nominal Scales Assignment to categories according to a rule
e. g., manic - depressive
paranoid - schizophrenic
involutional - melancholic
Starting point of science
Chemists - elements
Physicists - atoms and sub-atomic particles
Lineaus - biological categories
Freud - infantile sexuality - neurotic disorders
Modern Psychology
does it have reliable units of analysis?
Reflexes?
short term memory?
behavior disorders?

7. Frequency Distributions (Nominally Scaled Data)
Bar graph - histogram
Mode - summary statistic

8. Ordinal scales: - Numbers convey relative magnitude.
rank of one usually assigned to highest magnitude
can’t add or subtract ranks, e. g., ranks of weight
Rank: Weight (lbs.)
3 3
4 2

9. Ordinal Scales Summary Statistics:
Central Tendency: Median (as many observations above median as below it)
Variability: Range (difference between the smallest and highest values)

10. Interval scales:
Size of difference is known
Units are of equal size
Ratio scales:
True zero point exists
Multiplication or division possible

11. Magnitude of Psychological Judgments as a Function of Physical Intensity

12. CALCULATING THE MEAN
Given the raw data: 2, 4, 6, 8, 10

13. Arithmetic Mean = Center of Gravity

14. Symmetrical Distributions
Asymmetrical Distributions

15. Symmetrical Distributions

16. Skewed (Asymmetrical) Distrubutions

17. Measures of Central Tendency in a Positively Skewed Distribution

18. Binomial Distributions

19. CALCULATING DEVIATIONS FROM THE MEAN
Given the raw data: 2, 4, 6, 8, 10
Mean Deviation =
Mean Absolute Deviation =
Variance =
Standard Deviation =

20. MEASURING WITH THE STANDARD DEVIATION: Z- SCORES
Given the raw data: 2, 4, 6, 8, 10

21. CORRELATION

22. Normal Distribution

23. r = +1.0
r = -1.0 Zy Zy Zx Zx

24. Example of Positive Correlation

25. Examples of Positive, Negative and Minimal Correlation

26. Relationship Between r2 and Predicted Variance
Example: measures of rainfall and corn height
Suppose that r = 0.8. This means that 64% (0.8)2 of the variance of the height of corn height is accounted for by knowledge of how much rain fell.

27. VALIDITY AND RELIABILITY
Reliability: To what extent will a test give the same set of results over repeated measurements?
Validity: To what extent does a test measures what it purports to measure?
Validity and reliability are measured as correlation coefficients.

28. Measuring reliability:
Odd-even or split-half method: To what extent does one half of the test agree with the items of the second half of the test?
Test-retest: Results of test is given on two different occasions are compared. Assumes that there are no practice effects
Alternative form: Where there is a practice effect, an alternative form of the original test is given and the results are compared.
A reliable test may not be valid.
A valid test must be reliable may not be valid.
A valid test must be reliable.

29. HERITABILITY
Heritability: The proportion of variance of a phenotype that is attributable to genetic variance.
Phenotype: Observable trait
Genotype: What is transmitted from generation to generation
What % of a phenotype is genetic?
Hertiability is calculated by determining phenotypic variance and the magnitudes of its two components (genetic and environmental variance)

30. Calculation of Heritability
Heritability: The proportion of variance of a phenotype that is attributable to genetic variance.
2p = 2g + 2e 2 2 G E 1 + = 2 2 P P 2 G P = h2
(h2 > 0 < 1)
Heritability =

31. Which Contributes More to Area? Width or Length

32. Heritability

33. HERITABILITY DOES NOT. APPLY TO INDIVIDUALS. Example: h2 of IQ = 0. 6
HERITABILITY DOES NOT APPLY TO INDIVIDUALS! Example: h2 of IQ = This does not mean that 60% of an individual’s IQ is genetic and 40% is environmental.

34. Heritability

35. Heritability is Specific to the Population in which it’s Measured

36. 2
Minimum & maximum values of h (coefficient of heritability): h = 0.00: None of the observed values of phenotype is due to genes (all of it is due to environmental differences). h =1.00: All of variance is due to genes. __ G h2 =
(h2 > 0 < 1) 2 P

37. Examples Of Heritability Coefficients:. Piebald Holstein Cow;. h2 =
Examples Of Heritability Coefficients: Piebald Holstein Cow; h2 = .95 (color) h2 = .3 (milk production) Pigs: h2 = .55 (body fat) h2 = .15 (litter size) h2 is specific to the environment and population studied.

38. HERITABILITY ESTIMATES ARE SPECIFIC TO POPULATIONS AND ENVIRONMENTS IN WHICH THEY ARE MEASURED!
Example 1: Heritability of skin color in Norway and the United States. It’s higher in the United States. Why? Because, in Norway the environment contributes more to phenotypic variation than family background. In the United States family background contributes more to variation in skin color then the environment.

39. HERITABILITY ESTIMATES ARE SPECIFIC TO POPULATIONS AND ENVIRONMENTS IN WHICH THEY ARE MEASURED! Example 2: Heritability of Tuberculosis. Decreased during the 20th century because of changes in the environment. Up to and during the 19th century, everyone who was exposed to germ got sick if they were susceptible. Improved hygiene made it less likely that genetically disposed individuals will get TB. Thus, heritability of TB decreased as environmental diversity increased.

40. How to Reduce h2 1. Interbreed - this reduces 2g 2. Increase 2e
How to Reduce h2 1. Interbreed - this reduces 2g 2. Increase 2e. How to Increase h2 1. outcrossing - new genes 2. mutation - new genes 3. select for rare characteristics 4. reduce 2e.