You are studying the effectiveness of an advertisement designed to prevent teenagers from drinking. The advertisement is shown to 6 teenagers. Their attitude toward drinking is assessed at three times: prior to showing the ad, immediately following the ad, and two months after the ad. Those data are presented below Time of assessment Subject Before Immediately After Two Months Later 1 12 6 9 2 8 3 7 3 16 15 14 4 4 3 3 5 9 4 6 6 13 8 10 Source of Variation Sums of Squares df Mean Squares F Factors or Treatment *** *** *** *** Error *** *** *** Total *** *** (Suppose that assumptions required to perform a one-way analysis of variance have been tested positively.) Using the 1% significance level, test the hypothesis that the attitude towards drinking for teenagers before, immediately after and two months after the ad is the same. a. Calculate the missing values for the ANOVA table above.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
You are studying the effectiveness of an advertisement designed to prevent teenagers from drinking. The advertisement is shown to 6 teenagers. Their attitude toward drinking is assessed at three times: prior to showing the ad, immediately following the ad, and two months after the ad. Those data are presented below
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|
Time of assessment |
||
|
Subject |
Before |
Immediately After |
Two Months Later |
|
1 |
12 |
6 |
9 |
|
2 |
8 |
3 |
7 |
|
3 |
16 |
15 |
14 |
|
4 |
4 |
3 |
3 |
|
5 |
9 |
4 |
6 |
|
6 |
13 |
8 |
10 |
|
|
|
|
|
|
|
Source of Variation |
Sums of Squares |
df |
Mean Squares |
F |
|
Factors or Treatment |
*** |
*** |
*** |
*** |
|
Error |
*** |
*** |
*** |
|
|
Total |
*** |
*** |
|
|
(Suppose that assumptions required to perform a one-way analysis of variance have been tested positively.) Using the 1% significance level, test the hypothesis that the attitude towards drinking for teenagers before, immediately after and two months after the ad is the same.
a. Calculate the missing values for the ANOVA table above.
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