1. Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Spring 2017 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays & Fridays.
Welcome

2. A note on doodling

4. Lab sessions Everyone will want to be enrolled
in one of the lab sessions
Project 2
Presentations
continue

5. By the end of lecture today 3/6/17
Introduction to hypothesis testing
Interpreting
Alpha levels
p values
Type I and Type II Errors

6. Before next exam (April 7th)
Please read chapters in OpenStax textbook
Please read Chapters 2, 3, and 4 in Plous
Chapter 2: Cognitive Dissonance
Chapter 3: Memory and Hindsight Bias
Chapter 4: Context Dependence

7. No class on Friday Have a safe and happy spring break .
No homework over spring break

8. Whether or not feed had corn oil
No, feed had no corn oil
Yes, the feed had corn oil
Weight of eggs
60 grams if no corn oil
63 grams if corn oil
weight of eggs based on corn oil in food
weight of eggs based on corn oil in food
true experiment
between
nominal
ratio
200
100
100
198 99 99

9. -3.35
1.97
Yes
Yes
Yes
Yes
0.05
The weights of eggs for chickens who received the corn oil was 63
grams, while the weights of the eggs for chickens who did not receive
the corn oil was 60 grams. A t-test found this to be a significant
difference t(198) = -3.35; p < 0.05

10. Whether or not offered incentive
Was offered incentive
Was not offered incentive
Grade point average
2.3 for incentive group
2.1 for no incentive group
GPA based on incentive
GPA based on incentive
true experiment
between
nominal
interval
500
250
250
498
249
249

11. 3.64
1.964
Yes
Yes
Yes
Yes
0.05
The average GPA was 2.3 for students who were offered an incentive
and was 2.1 for students who were not offered an incentive.
A t-test was completed and we found this to be a significant
difference t(498) = 3.64; p < 0.05

12. Whether or not video included sound
Video with no sound
Video with sound
Number of items correctly recalled
3.7 for video with no sound
3.3 items for video with sound
number of items recalled
number of items recalled
true experiment
between
nominal
ratio 40 20 20 38 19 19

13. 1.17
2.02 No No No
0.248 No
0.05
The average number of items recalled was 3.7 for the students who
watched the ads with no sound, and was 3.3 for students who
watched video with sound. A t-test was completed and we found
no significant difference t(38) = 1.17; p < 0.05

14. Location of air conditioner plant
Japan
United States
Turnover rate
3.12% turnover rate for Japan
6.56% turnover rate for USA
turnover rates between Japan and USA
turnover rates between Japan and USA
quasi
between
nominal
ratio 10 5 5 8 4 4

15. -4.46
2.31
Yes
Yes
Yes
0.0021
Yes
0.05
The average turnover rate in the Japanese plants is 3.12 while the
average turnover rated in the American plants is A t-test
showed a significant difference, t(8) = ; p < 0.05

16. Rejecting the null hypothesis
The result is “statistically significant” if:
the observed statistic is larger than the critical statistic (which can be a ‘z” or “t” or “r” or “F” or x2)
observed stat > critical stat If we want to reject the null, we want our t (or z or r or F or x2) to be big!!
the p value is less than 0.05 (which is our alpha)
p < If we want to reject the null, we want our “p” to be small!!
we reject the null hypothesis
then we have support for our alternative hypothesis

17. Confidence Interval of 95% Has and alpha of 5% α = .05
Critical z
-2.58
Critical z
2.58
Confidence Interval of 99%
Has and alpha of 1%
α = .01
99%
Area in the tails is called alpha
Critical z
-1.96
Critical z
1.96
Confidence Interval of 95% Has and alpha of 5% α = .05
95%
Critical Z separates rare from common scores
Critical z
-1.64
Critical z
1.64
Confidence Interval of 90%
Has and alpha of 10%
α = . 10
90%

18. Deciding whether or not to reject the null hypothesis. 05 versus
Deciding whether or not to reject the null hypothesis .05 versus .01 alpha levels
What if our observed z = 2.0?
How would the critical z change?
α = 0.05
Significance level = .05
α = 0.01
Significance level = .01
-1.96 or
+1.96
p < 0.05
Yes, Significant difference
Reject the null
Remember,
reject the null if the observed z is bigger than the critical z
-2.58 or
+2.58
Not a Significant difference
Do not Reject the null

19. Deciding whether or not to reject the null hypothesis. 05 versus
Deciding whether or not to reject the null hypothesis .05 versus .01 alpha levels
What if our observed z = 1.5?
How would the critical z change?
α = 0.05
Significance level = .05
α = 0.01
Significance level = .01
-1.96 or
+1.96
Do Not
Reject the null
Not a Significant difference
Remember,
reject the null if the observed z is bigger than the critical z
-2.58 or
+2.58
Not a Significant difference
Do Not
Reject the null

20. 90% Moving from descriptive stats into inferential stats….
For scores that fall into the middle range,
we do not reject the null
Moving from descriptive stats
into inferential stats….
Critical z
1.64
Critical z
-1.64
90%
Measurements that occur within the middle part of the curve are ordinary (typical) and probably belong there 5% 5%
Measurements that occur outside this middle ranges are suspicious, may be an error
or belong elsewhere
For scores that fall into the regions of rejection,
we reject the null
What percent of the distribution will fall in region of rejection
Critical
Values

21. Rejecting the null hypothesis
The result is “statistically significant” if:
the observed statistic is larger than the critical statistic
observed stat > critical stat If we want to reject the null, we want our t (or z or r or F or x2) to be big!!
the p value is less than 0.05 (which is our alpha)
p < If we want to reject the null, we want our “p” to be small!!
we reject the null hypothesis
then we have support for our alternative hypothesis
A note on decision making following procedure
versus being right relative to the “TRUTH”

22. Procedures versus outcome Best guess versus “truth”.
Decision making:
Procedures versus outcome
Best guess versus “truth”
What does it mean to be correct?
Why do we say:
“innocent until proven guilty”
“not guilty” rather than “innocent”
Is it possible we got a verdict wrong?

23. Thank you!
See you next time!!