2. Practice
As part of a program to reducing smoking, a national organization ran an advertising campaign to convince people to quit or reduce their smoking. To evaluate the effectiveness of their campaign, they had 15 subjects record the average number of cigarettes smoked per day in the week before and the week after exposure to the advertisement. Determine if the advertisements reduced their smoking (Alpha = .05).

3. Practice Subject Before After 1 45 43 2 16 20 3 17 4 33 30 5 25 6 19 734 8 28 9 26 23 10 40 41 11 12 36 13 15 14 32

4. Practice Dependent t-test t = .45 Do not reject Ho
The advertising campaign did not reduce smoking

5. Practice
You wonder if there has been a significant change (.05) in grading practices over the years.
In 1985 the grade distribution for the school was:

6. Practice
Grades in 1985
A: 14%
B: 26%
C: 31%
D: 19%
F: 10%

7. Grades last semester

8. Step 1: State the Hypothesis
H0: The data do fit the model
i.e., Grades last semester are distributed the same way as they were in 1985.
H1: The data do not fit the model
i.e., Grades last semester are not distributed the same way as they were in 1985.

9. Step 2: Find 2 critical
df = number of categories - 1

10. Step 2: Find 2 critical df = number of categories - 1 df = 5 - 1 = 4
 = .05
2 critical = 9.49

11. Step 3: Create the data table

12. Step 4: Calculate the Expected Frequencies

13. Step 5: Calculate 2
O = observed frequency
E = expected frequency

14. 2
6.67

15. Step 6: Decision Thus, if 2 > than 2critical
Reject H0, and accept H1
If 2 < or = to 2critical
Fail to reject H0

16. Step 6: Decision Thus, if 2 > than 2critical
2 = 6.67
2 crit = 9.49
Step 6: Decision
Thus, if 2 > than 2critical
Reject H0, and accept H1
If 2 < or = to 2critical
Fail to reject H0

17. Step 7: Put answer into words
H0: The data do fit the model
Grades last semester are distributed the same way (.05) as they were in 1985.

19. The Three Goals of this Course
1) Teach a new way of thinking
2) Self-confidence in statistics
3) Teach “factoids”

21. Mean But here is the formula == so what you did was
= 320
320 / 4 = 80

22. r =
tobs = (X - ) / Sx
r =

23. What you have learned! Introduced to statistics and learned key words
Scales of measurement
Populations vs. Samples

24. What you have learned!
Learned how to organize scores of one variable using:
frequency distributions
graphs
measures of central tendency

25. What you have learned! Learned about the variability of distributions
range
standard deviation
variance

26. What you have learned! Learned about combination statistics z-scores
effect sizes
box plots

27. What you have learned!
Learned about examining the relation between two continous variables
correlation (expresses relationship)
regression (predicts)

28. What you have learned!
Learned about probabilities

29. What you have learned! Learned about the sampling distribution
central limit theorem
determine probabilities of sample means
confidence intervals

30. What you have learned! Learned about hypothesis testing
using a t-test for to see if the mean of a single sample came from a population value

31. What you have learned! Extended hypothesis testing to two samples
using a t-test for to see if two means are different from each other
independent
dependent

32. What you have learned!
Extended hypothesis testing to three or more samples
using an ANOVA to determine if three or means are different from each other

33. What you have learned! Extended ANOVA to two or more Ivs
Factorial ANOVA
Interaction
Extended ANOVA with repeated measures

34. What you have learned! Learned how to examine nominal variables
Chi-Square test of independence
Chi-Square test of goodness of fit

35. CRN:

37. Next Step Nothing new to learn!
Just need to learn how to put it all together

38. Four Step When Solving a Problem
1) Read the problem
2) Decide what statistical test to use
3) Perform that procedure
4) Write an interpretation of the results

39. Four Step When Solving a Problem
1) Read the problem
2) Decide what statistical test to use
3) Perform that procedure
4) Write an interpretation of the results

40. Four Step When Solving a Problem
1) Read the problem
2) Decide what statistical test to use
3) Perform that procedure
4) Write an interpretation of the results

41. How do you know when to use what?
If you are given a word problem, would you know which statistic you should use?

42. Example
An investigator wants to predict a male adult’s height from his length at birth. He obtains records of both measures from a sample of males.

43. Possible Answers a. Independent t-test m. Regression
b. Dependent t-test n. Standard Deviation
c. One-Sample t-test o. Z-score
d. Goodness of fit Chi-Square p. Mode
e. Independence Chi-Square n q. Mean
f. Confidence Interval r. Median
g. Correlation (Pearson r) s. Bar Graph
h. Scatter Plot t. Range
j. Line Graph u. ANOVA
k. Frequency Polygon v. Factorial ANOVA
l. Histogram

44. Example
An investigator wants to predict a male adult’s height from his length at birth. He obtains records of both measures from a sample of males.
Use regression

45. Cookbook
Due: Final exam
Early grade: Monday!