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(a) What are the independent and dependent variables? (b) From the scatter plot, is there evidence that a linear regression would not be suitable for this dataset? (c) Use the regression summary to write an equation for the line of best fit. (d) At the a = has an impact on final mark? State the relevant null and alternative hypotheses. 0.05 significance threshold, is there evidence that tutorial attendance

(a) What are the independent and dependent variables? (b) From the scatter plot, is there evidence that a linear regression would not be suitable for this dataset? (c) Use the regression summary to write an equation for the line of best fit. (d) At the a = has an impact on final mark? State the relevant null and alternative hypotheses. 0.05 significance threshold, is there evidence that tutorial attendance

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 6PPS
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Df Sum Sq Mean Sq F-value p-value X 1 4393 4393 24.16 6.65e-06 Residuals 63 11455 182 Table 3: Q10) ANOVA table. Normal Q-Q Residuals vs Fitted 370 8. 8 025 62° 062 T T -2 -1 1 2 50 55 60 65 70 75 Theoretical Quantiles Fitted values Im(Y - X) Im(Y ~ X) Figure 4: Q10) QQ-plot. Figure 5: Q10) Residual plot. (a) What are the independent and dependent variables? (b) From the scatter plot, is there evidence that a linear regression would not be suitable for this dataset? (c) Use the regression summary to write an equation for the line of best fit. (d) At the a has an impact on final mark? State the relevant null and alternative hypotheses. 0.05 significance threshold, is there evidence that tutorial attendance (e) If I attend 3 more tutorials, what impact do I expect this to have on my final mark? (f) Is there evidence of non-normality or unequal variance in the residuals? What does this lead you to say about the validity of the model? (g) The R2 value for the model fit was 0.11. Write a sentence about what this represents with respect to the data. opo 6o 00 o do O o o 10 20 30 O 0- Residuals -1 Standardized residuals
Transcribed Image Text:Df Sum Sq Mean Sq F-value p-value X 1 4393 4393 24.16 6.65e-06 Residuals 63 11455 182 Table 3: Q10) ANOVA table. Normal Q-Q Residuals vs Fitted 370 8. 8 025 62° 062 T T -2 -1 1 2 50 55 60 65 70 75 Theoretical Quantiles Fitted values Im(Y - X) Im(Y ~ X) Figure 4: Q10) QQ-plot. Figure 5: Q10) Residual plot. (a) What are the independent and dependent variables? (b) From the scatter plot, is there evidence that a linear regression would not be suitable for this dataset? (c) Use the regression summary to write an equation for the line of best fit. (d) At the a has an impact on final mark? State the relevant null and alternative hypotheses. 0.05 significance threshold, is there evidence that tutorial attendance (e) If I attend 3 more tutorials, what impact do I expect this to have on my final mark? (f) Is there evidence of non-normality or unequal variance in the residuals? What does this lead you to say about the validity of the model? (g) The R2 value for the model fit was 0.11. Write a sentence about what this represents with respect to the data. opo 6o 00 o do O o o 10 20 30 O 0- Residuals -1 Standardized residuals
You have been asked to analyse a suspected relationship between tutorial attendance and final marks for a university course. The latest set of data includes final marks Y (between 0 and 100) and tutorial attendance X (between 0 and 12) for 65 students. You have done a regression analysis on the dataset in R and the output is given below, along with a scatter plot of X and Y. Answer the subsequent questions regarding this analysis. 8. 2 4 6 8 10 12 Tutorials Attended Figure 3: Q3) Scatterplot of marks against tutorial attendance. Estimate Std. Error t value Pr(> |t|) (Intercept) 44.1517 4.6207 9.555 7.17e-14 X 2.7914 0.5679 4.915 6.65e-06 Table 2: Q10) Regression summary. 000 00 00 00 O O0 O OO 00 O O o o 08 09 40 Final Mark
Transcribed Image Text:You have been asked to analyse a suspected relationship between tutorial attendance and final marks for a university course. The latest set of data includes final marks Y (between 0 and 100) and tutorial attendance X (between 0 and 12) for 65 students. You have done a regression analysis on the dataset in R and the output is given below, along with a scatter plot of X and Y. Answer the subsequent questions regarding this analysis. 8. 2 4 6 8 10 12 Tutorials Attended Figure 3: Q3) Scatterplot of marks against tutorial attendance. Estimate Std. Error t value Pr(> |t|) (Intercept) 44.1517 4.6207 9.555 7.17e-14 X 2.7914 0.5679 4.915 6.65e-06 Table 2: Q10) Regression summary. 000 00 00 00 O O0 O OO 00 O O o o 08 09 40 Final Mark
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