We Have Numbers Of Free Samples

Quantitative Data Representation

In this study, researcher has chosen seven variables named age, educ, gender, Meduc, Feduc, tvhours, parented. Age, gender are the independent variables. Edu, Meduc, Feduc, tvhours and parented are the dependant variables.

Q1.  Between what age people watch the television most?

ANOVA^a

a. Dependent Variable: MOTHER’S HIGHEST YEAR SCHOOL COMPLETED

                            b. Predictors: (Constant), AGE OF RESPONDENT

Coefficients^a

a. Dependent Variable: MOTHER’S HIGHEST YEAR SCHOOL COMPLETED

1. The value of Sig is 0.000. Therefore, it is smaller than 0.05 which is the standard value.  Here, null hypothesis is rejected.

2. Regression coefficient in the multiple regressions can be denoted as slope of linear relationship with criterion variable and part of the predictor variable. Here, value of B is -0.050. Value of Beta is -0.220. This supports the literature that some of the people watch more television than others.

3. The value of R is 0.220 and value of R square and adjusted R square is 0.048, which is more than 0 (The standard value of r square). Therefore, the job has been done perfectly.

4. Assumption of Regression model

The value of R is 0.220 which is positive. It has shown a perfectly linear ascending relationship between independent and dependant variables.

Q2. What is the highest year of school completed by the respondent?

ANOVA^a

a. Dependent Variable: HIGHEST YEAR OF SCHOOL COMPLETED

                                    b. Predictors: (Constant), AGE OF RESPONDENT

Coefficients^a

1. The value of Sig is 0.479. Therefore, it is greater than 0.05.  Here, null hypothesis is not rejected.

2. Here, value of B is -0.002. Value of Beta is -0.014 this supports the literature that some of the people watch more television than others.

3. The value of R is 0.014 and value of R and adjusted R square is 0.000, which is equals 0. Therefore, the job has been done perfectly.

4. Assumption of Regression model

The value of R is 0.014 which is positive. It has shown a perfectly linear ascending relationship between independent and dependant variables.

Q3. What is the gender of the respondent?

ANOVA^a

Coefficients^a

1. The value of Sig is 0.773. Therefore, it is greater than 0.05. Here, null hypothesis is not rejected.

2. Here, value of B is -0.035. Value of Beta is -0.006. Standard error is -0.006.

3. The value of R is 0.006 and value of R and adjusted R square is 0.000, which is equals 0. Therefore, the job has been done perfectly.

4. Assumption of Regression model

The value of R is 0.006 which is positive. It has shown a perfectly linear ascending relationship between independent and dependant variables.

Q4. What is the highest year of school completed by mother of the respondent?

ANOVA^a

Coefficients^a

1. The value of Sig is 0.000. Therefore, it is lower than 0.05. Here, null hypothesis is rejected.

2. Here, value of B is -0.050. Value of Beta is -0.220. Standard error is 0.005

3. The value of R is 0.220 and value of R and adjusted R square is 0.048, which is positive. Therefore, the job has been done perfectly.

4. Assumption of Regression model

The value of R is 0.220 which is positive. It has shown a perfectly linear ascending relationship between independent and dependant variables.

Q5. What is the highest year of school completed by father of the respondent?

ANOVA^a

Coefficients^a

1. The value of Sig is 0.000. Therefore, it is lower than 0.05. Here, null hypothesis is rejected.

2. Here, value of B is -0.059. Value of Beta is -0.239. Standard error is 0.006

3. The value of R is 0.239 and value of R and adjusted R square is 0.057, which is positive. Therefore, the job has been done perfectly.

4. Assumption of Regression model

The value of R is 0.239 which is positive. It has shown a perfectly linear ascending relationship between independent and dependant variables.

Q6. How many hours per day respondent watch television?

ANOVA^a

Coefficients^a

1. The value of Sig is 0.476. Therefore, it is greater than 0.05. Here, null hypothesis is not rejected.

2. Here, value of B is -0.091. Value of Beta is -0.017. Standard error is 0.127

3. The value of R is 0.017and value of R and adjusted R square is 0.000, which is equals to zero. Therefore, the job has been done perfectly.

4. Assumption of Regression model

The value of R is 0.017 which is positive. It has shown a perfectly linear ascending relationship between independent and dependant variables.

Q7. What is the highest education of the parents of respondent?

ANOVA^a

Coefficients^a

1. The value of Sig is 0.127. Therefore, it is greater than 0.05. Here, null hypothesis is not rejected.

2. Here, value of B is 27.282. Value of Beta is 0.030. Standard error is 17.861

3. The value of R is 0.030 and value of R and adjusted R square is 0.001, which is positive. Therefore, the job has been done perfectly.

4. Assumption of Regression model

The value of R is 0.030 which is positive. It has shown a perfectly linear ascending relationship between independent and dependent variables.

Durbin Watson

Model Summary^b

ANOVA^a

Coefficients^a

Residuals Statistics^a

Descriptive Statistics

Correlations

**. Correlation is significant at the 0.01 level (2-tailed).

5. This table has shown multiple linear regression summaries and the overall statistics. It has been found that the value of R is 0.036 and R square is 0.001. This indicates that linear regression is 0.1%. The Durbin Watson d = 1.914, which is between two critical values of 1.5 and 2.5. Therefore, it can be assumed that there is no such first order linear type of auto correlation in taken linear regression data.

In case, researcher would force all of the variables in linear regression model, the value of r square and adjusted r square would be slightly higher.

Next table is the F test table.  The value of null hypothesis of this table can explain the zero variance of dependent variable.  However, it can be said that F test is crucially significant and this model can explain significant amount of variance within the rate of people who are attracted to television.

Appendices

Appendix 1: SPSS tests

Q1.  Between what age people watch the television most?

Model Summary

 

Q2. What is the highest year of school completed by the respondent?

Model Summary

 

Q3. What is the gender of the respondent?

Model Summary

 

Q4. What is the highest year of school completed by mother of the respondent?

 

Q5. What is the highest year of school completed by father of the respondent?

 

Q6. How many hours per day respondent watch television?

 

Q7. What is the highest education of the parents of respondent?

[Download not found]

Download