# States Project Harvard Case Solution & Analysis

## States Project Case Study Solution

### Table 4.3 Correlation Matrix

 Correlations C L TM P C Pearson Correlation 1 .447** .573** .518** Sig. (2-tailed) .000 .000 .000 N 200 200 200 200 L Pearson Correlation .447** 1 .326** .298** Sig. (2-tailed) .000 .000 .000 N 200 200 200 200 TM Pearson Correlation .573** .326** 1 .516** Sig. (2-tailed) .000 .000 .000 N 200 200 200 200 P Pearson Correlation .518** .298** .516** 1 Sig. (2-tailed) .000 .000 .000 N 200 200 200 200 **. Correlation is significant at the 0.01 level (2-tailed).

### Analyzing relationship of variables with Multiple Regression

The regression analysis shows the relationship of dependent variable and independent variable with each other. It signifies the impact of independent factors with dependent factor. The study is to investigate the relationship and impact of independent variables Trustworthiness, like ability and Familiarity with dependent variable Purchase intention.

### Table 4.4.1

 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .918a .843 .813 .4711 a. Predictors: (Constant), SP, TM, L

Table 4.4.1 shows the model summary of regression analysis. The value of R2  is observed here which should be > 0.7 to show the impact of independent variable on dependent variable. The results explain that R2 is 0.834 which is on moderate level that independent variables are impacting the dependent variable on moderate level.

### Table 4.4.2

 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 19.031 3 6.344 28.582 .000b Residual 3.551 16 .222 Total 22.582 19 a. Dependent Variable: C b. Predictors: (Constant), SP, TM, L

An ANOVA test is conducted in SPSS to find more the significance of variable. It is the analysis of variance where we test the value of F test which should be greater >2. Table 4.4.2, shows the value of F test is 28.582 which is > 2 and indicates that the model is significant.

### Table 4.4.3

 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .404 .406 .996 .334 L .968 .173 .870 5.586 .000 TM -.259 .118 -.247 -2.196 .043 SP .173 .146 .176 1.182 .254 a. Dependent Variable: C

Table 4.4.3 shows the results of regression analysis based on the value of t-test and significance. The decision criteria are t-test should be > 2 and probability must be < 0.05. The results of coefficients indicate that Covid-19 possesses t-test  .996 which is > 2 and probability 0.334< 0.05 which is significant variable. Learning (L) possesses t-test 5.586 which is < 2 and probability 0.000> 0.05 which is insignificant variable. Teaching methods (T) possesses t-test -2.196 which is >2 and probability 0.000 < 0.05 which is significant variable.

### 4.5 Hypothesis Testing

 Alternative Hypothesis T Statistics Significant level Decision H1: There is a significant influence of Covid-19 on the learning of students 5.58 .000 Accepted H2: There is a significant influence of Covid-19 on teaching methods? -2.196 .043 Accepted H3: There is a significant influence of Covid-19 have on the productivity of students? 1.182 .254 Not Accepted

Discussion and Conclusion

This Analysis was done to analyze the impact of Covid-19 on learning, teaching methods and students productivity. As due to Covid-19 education sector was most affected sector of the country. It was first time for students as well as teachers to take class virtually. In the analysis we tested the hypothesis through t test and also applied multiple regression and correlation. We found that the hypothesis 1 was accepted because the t-value should be greater than 1.96. and the t-statistics of H1 was 5.58 and was significant with .000.

In the same way the H2 was also accepted with (T-states -2.196 & sign .043), which was also accepted. H3 was not acceptable because it was not significat. The prime purpose is to conduct a survey where the Covid-19 impact was analyzed on learning, teaching methods and Students productivity. The research was conducted from 20 teachers to collect the data.

We conclude that Due to Covid-19 Countries imposed lockdown which affected education sector. Due to Covid-19 students were not able to join the classes and understand the concepts effectively. Whereas it hurts students learning. And due to covid-19 teachings methods were also changed and that was totally new for teachers as well as students which took time for both to adjust and understand. Along students productivity was also affected.

Although, the interpretation is done on the ground of standard tools like T test, F test, significance, R2 and Cronbach alpha. So far the results are concerned;Covid-19 have the positive impact on Learning, Teaching Methods and students productivity.

### What I meant Statement:

(Student 1)During this whole project, as a student of Statistics I learned that the quantitative parts which we covered in the course, actually play huge role in our daily practical life. We learned that how the applied statistics works and how we can estimate situations and how these situations help us to make future planning. The tests which we learned in the class, or the descriptive which we interpreted previously, how we can use them in real world...............

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