Question

TVHOURS	OBEDIENCE	ATTITUDE
3	1	2
1	1	1
4	1	1
4	1	1
7	1	1
2	1	1
7	1	1
14	1	3
3	1	1
3	2	2
2	2	2
3	3	2
3	3	2
5	2	2
5	1	2
2	2	1
2	1	1
2	1	1
2	1	1
2	3	2
2	2	2
4	2	2
3	2	2
10	1	2
4	1	1
10	1	2
2	1	1
2	1	2
4	1	1
4	1	1

Hypothesis Question: Does Television Viewing Encourage Aggression in Children?

1.)How many hours a day on average that each child watches television? 4.033333 hours

2.) What is the range of television hours watched? 13

3.) In computing the mean hours watched, were there any apparent outliers? Use the formula of 1.5*IQR + Q3. What effect might this have on the mean hours watched? x=10; max=14; The outliers "pull" the mean value of the number of TV hours watched higher.

4.) Recompute the mean without the outlier(s). 3.22222222

5.)Using a linear regression analysis, what 'kind' of correlation does the data suggest between the numbers of hours of TV hours watched and the obedience? slope: -0.062491564313673; Ccorrelation coefficient: 0.26861422465844; Negative correlation, indicating an inverse relationship . As one variable goes up, the other goes down

6.) What is the correlation coefficient (r value) between TV hours watched and attitude? (r value): 0.4233

Question:Do a simple frequency count on attitude. What fundamental problem does this data present for the hypothesis? What sampling changes could be made to better test the hypothesis that “children who watch more TV are more aggressive?”

I need the answer to the question:

Do a simple frequency count on attitude. What fundamental problem does this data present for the hypothesis? What sampling changes could be made to better test the hypothesis that “children who watch more TV are more aggressive?”

Answer 1

1.)How many hours a day on average that each child watches television?

Ans: 4.033333 hours

2.) What is the range of television hours watched?

Ans: Range=Maximum - Minimum=14-1= 13

3.) In computing the mean hours watched, were there any apparent outliers? Use the formula of 1.5*IQR + Q3. What effect might this have on the mean hours watched?

Ans: Q1=2, Q2=3, and Q3= 4.25

IQR= Q3-Q1=2.25

1.5*IQR + Q3=1.5*2.25+4.25=7.625

The outlier observations are the observation which is greater than 7.625. So the outliers are 10, 10, and 14.

The outliers "pull" the mean value of the number of TV hours watched higher.

4.) Recompute the mean without the outlier(s).

Ans: The mean without outliers is 3.22222222

5.)Using a linear regression analysis, what 'kind' of correlation does the data suggest between the numbers of hours of TV hours watched and the obedience?

Ans: slope: -0.062491564313673;

Correlation coefficient: - 0.26861422465844;

Negative correlation, indicating an inverse relationship. As one variable goes up, the other goes down.

6.) What is the correlation coefficient (r value) between TV hours watched and attitude? (r value):

Ans: r=0.4233

P​​​ositive correlation, indicating a direct relationship. As one variable goes up, the other also goes up.

Question: Do a simple frequency count on attitude. What fundamental problem does this data present for the hypothesis? What sampling changes could be made to better test the hypothesis that “children who watch more TV are more aggressive?”

Ans:

The histogram of the variable attitude shows that this variable does not follow a normal distribution (the histogram does not have in symmetric shape). So, the estimation of the correlation coefficient on 6) does not valid. Also, we can not apply the simple regression model for the variables TV hours watched and attitude. The best way to test the hypothesis that “children who watch more TV are more aggressive is to apply the multinomial logistic regression model where variable attitude as a response variable (it has three outcome values 1,2 and 3)