Question

In: Statistics and Probability

In this case, estimate the impact of certain factors on a variable of interest through linear...

In this case, estimate the impact of certain factors on a variable of interest through linear regression. We are interested in finding out which factors have an impact on students’ grades in a stats course (dependent variable). Which independent variables would you include? State variables you chose to include and explain what kind of impact (positive or negative) you think it would have on the students grades and why.

Solutions

Expert Solution

There are several independent variables which can impact the dependent variable, students' grades here:

1) No. of hours studied per week - Expected to have a positive impact since more study generally translates into better grades

2) Experience of Faculty - Higher experience of faculty is expected to positively impact the students' grades as the quality of education imparted will be better

3) Involvement in co-curricular activities - Expected to positively impact grades as students will feel more energized and attentive at studies if involved in co-curricular activities.

4) Family stability - This is a social factor, expected to positively impact grades if a student's family is more stable and supportive.

5) Economic condition - Family's economic condition is another factor, having a positive impact if the family is economically stable

6) Attention span - this is an individual trait, a higher attention span has a positive impact on student's grades

7) Prior education - This is another factor that might affect grades positively if the prior education quality is good.

8) Attendance - Higher attendance generally translates into higher grades for the students as a student with higher attendance record is expected to be aware of the syllabus and concepts better than others.


Related Solutions

What factors impact the quality of a bottom-up estimate? Discuss at least four factors – 300...
What factors impact the quality of a bottom-up estimate? Discuss at least four factors – 300 words.
Estimate a multiple linear regression relationship with the U.K. stock returns as the dependent variable, and...
Estimate a multiple linear regression relationship with the U.K. stock returns as the dependent variable, and U.K. Corporate Bond yield (Interest rate), U.S. Stock Returns, and Japan Stock Returns as the independent variables using the monthly data covering the sample period 1980-2017 (Finding the determinants of U.K. stock returns). Show the estimated regression relationship Conduct a t-test for statistical significance of the individual slope coefficients at the 1% level of significance. Provide the interpretation of the significant slope estimates. Conduct...
In a multi linear regression case study, the dependent variable is house_value, the independent variables are...
In a multi linear regression case study, the dependent variable is house_value, the independent variables are house_age, crime_rate, tax_rate, trying to build a model to predict the house value, how to state model assumptions? What's the assumption in this case? Thanks!
Estimate a multiple linear regression relationship with the U.K. stock returns as the dependent variable (intercept), and RBUK, U.S.
SUMMARY OUTPUT Regression Statistics Multiple R 0.727076179 R Square 0.528639771 Adjusted R Square 0.525504337 Standard Error 3.573206748 Observations 455 ANOVA df SS MS F Significance F Regression 3 6458.025113 2152.67504 168.601791 2.7119E-73 Residual 451 5758.280717 12.7678065 Total 454 12216.30583 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 99.0% Upper 99.0% Intercept -0.250148858 0.359211364 -0.6963835 0.48654745 -0.9560846 0.45578693 -1.1793476 0.67904987 RBUK 0.025079378 0.023812698 1.05319345 0.29281626 -0.0217182 0.07187699 -0.0365187 0.08667745 RSUS 0.713727515 0.042328316 16.8617037 8.0578E-50 0.6305423 0.79691273 0.60423372 0.82322131...
linear equation in two variable
Complete the following activity to solve the simultaneous equations.5x + 3y = 9 -----(I)2x - 3y = 12 ----- (I)
Linear Regression Linear regression is used to predict the value of one variable from another variable....
Linear Regression Linear regression is used to predict the value of one variable from another variable. Since it is based on correlation, it cannot provide causation. In addition, the strength of the relationship between the two variables affects the ability to predict one variable from the other variable; that is, the stronger the relationship between the two variables, the better the ability to do prediction. What is one instance where you think linear regression would be useful to you in...
If a variable is exponentially increasing, then the logarithm of that variable would have a linear...
If a variable is exponentially increasing, then the logarithm of that variable would have a linear trend. You are not convinced that fitting a trend line would bring a good forecast. Why would you think so? Why fitting a trend line on logarithm may not generate good forecasts in this case?
If a variable is exponentially increasing, then the logarithm of that variable would have a linear...
If a variable is exponentially increasing, then the logarithm of that variable would have a linear trend. You are not convinced that fitting a trend line would bring a good forecast. Why would you think so? Why fitting a trend line on logarithm may not generate good forecasts in this case?
What factors impact attraction?
What factors impact attraction?
How can we use “linear regression” to estimate non-linear functional forms?
How can we use “linear regression” to estimate non-linear functional forms?
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT