1 / 31

# PRED 35 4 TEACH. PROBILITY &amp; STATIS. FOR PRIMARY MATH

PRED 35 4 TEACH. PROBILITY &amp; STATIS. FOR PRIMARY MATH. Lesson 3 Central Tendency &amp; Variability. PRED 35 4 TEACH. PROBILITY &amp; STATIS. FOR PRIMARY MATH.

## PRED 35 4 TEACH. PROBILITY &amp; STATIS. FOR PRIMARY MATH

An Image/Link below is provided (as is) to download presentation Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

### Presentation Transcript

1. PRED 354 TEACH. PROBILITY & STATIS. FOR PRIMARY MATH Lesson 3 Central Tendency & Variability

2. PRED 354 TEACH. PROBILITY & STATIS. FOR PRIMARY MATH Q1. A researcher examined the effect of amount of relaxation training on insomnia. Four treatment groups were used. Subjects received relaxation training for 2, 4, or 8 sessions. A control group received no training (0 sessions). Following training, the researcher measured how long it took the subjects to fall asleep. The average time for each group is presented in the following table:

3. PRED 354 TEACH. PROBILITY & STATIS. FOR PRIMARY MATH Q1. a. Identify the IV and DV for this study. b. What is scale of the measurement was used for the IV and the DV? c. If the researcher used a graph to show the obtained relationship between the IV and the DV, what kind of graph would be appropriate? Sketch the graph showing the results of this experiment?

4. PRED 354 TEACH. PROBILITY & STATIS. FOR PRIMARY MATH Q2. For the following set of the scores 4, 6, 9, 5, 3, 8, 9, 4, 2, 5, 10, 7, 4 ,9, 8, 3 a. Construct a frequency distribution table b. Sketch a polygon showing the distribution c. Describe the shape of the distribution d. What is the percentile rank for X=6? e. What is the 70th percentile?

5. Central tendency is a statistical measure that identifies a single score as representative of an entire distribution. MEAN MEDIAN MODE

6. The Mean The mean for a distribution is the sum of the scores divided by the number scores.

7. Charactistics of the Mean 1. Changing a score or introducing a new score. 2. Adding or subtracting a constant from each score. 3. Multiplying or dividing each score by a constant.

8. The Median is the score that divides a distribution exactly in half. Three types of data? • When N is odd number • When N is even number • When there are several scores with the same value in the middle of the distribution.

9. The Median EX: • 3, 5, 8, 10, 11 • 3, 3, 4, 5, 7, 8 • 1, 2, 2, 3, 4, 4, 4, 4, 4, 5 EX: Find the median for this data 3, 4, 3, 2, 1, 3, 2, 4

10. The Mode In a frequency distribution, the mode is the score or category that has greatest frequency.

11. How do you decide which measure of central tendency to use? When to use mode? It can be used with any scale of measurement.

12. How do you decide which measure of central tendency to use? When to use median? • There are a few extreme scores in the distribution • Some scores have undetermined values • There are open ended distribution • The data measured on an ordinal scale

13. How do you decide which measure of central tendency to use? When to use median? • There are a few extreme scores in the distribution

14. How do you decide which measure of central tendency to use? When to use median? • Some scores have undetermined values

15. How do you decide which measure of central tendency to use? When to use median? • There are open ended distribution

16. Central tendency and the shape of the distribution 1. Symmetrical distribution 2. Skewed distributions

17. Central tendency EX: Find the mode, median and mean

18. Variability provides a quantitative measure of the degree to which scores in a distribution are spread out or clustered together. A. RANGE – B. SEMI-INTERQUARTILE RANGE C. STANDARD DEVIATION PURPOSE: Are the scores all clustered together, or are they scattered over a wide range of values?

19. Range The range is the distance between the largest score and the smallest score in the distribution. range = URL Xmax – LRL Xmin Ex. 3, 7, 12, 8, 5, 10

20. The Interquartile range and semi-interquartile range The interquartile range is the distance between the first quartile and the third quartile. interquartile range = Q3 – Q1 semi-interquartile range= ½ * (Q3 – Q1) Ex. 2, 3, 4, 4, 5, 5, 6, 6, 6, 7, 7, 8, 8, 9, 10, 11

21. Standard deviation and variance for a population (a measure of distance from the mean) Step 1. The first step in finding the standard distance from the mean is to determine the deviation for each individual score. Deviation is the distance from the mean Deviation score = X - µ

22. Standard deviation and variance for a population Step 2. The next step is to calculate the mean of the deviation scores. Step 3. Use mean squared deviation (Variance) Population Variance = Mean squared deviation = SS/N (SS = Σ (X - µ)2)

23. Standard deviation and variance for a population Step 4. Simply make a correction for having squared all the distances. standard deviation = √variance σ = √SS/N σ2 = SS/N EX:

24. Standard deviation and variance for a population Use the following population of scores to calculate SS, variance, and standard deviation Scores: 1, 9, 5, 8, 7 EX:

25. Standard deviation and variance for a sample Notations: Notice that these sample formula use n-1 instead of n.

26. Standard deviation and variance for a sample Why do we use n-1 for the sample? Sample variability tends to underestimate population variability unless some correction is made. Dividing by a smaller value produces a larger result and makes sample variability an accurate, or unbiased, estimator of population variability.

27. Standard deviation and variance for a sample Degrees of freedom: n-1 df = n-1 s2=SS/df s = √SS/df

28. Properties of SD 1. descriptive measure: distance from the mean 2. a measure of how big the error will be.

29. Properties of SD 1. Adding a constant to each score will not change the SD. 2. Multiplying each score by a constant causes the SD to be multiplied by the same constant.

30. SD or Range? When? 1. Extreme scores. 2. Sample size. 3. Stability under sampling 4. Open-ended distributions

31. SD or Range? When?

More Related