T_101_HW5_2023 × f 2023 Topic 12: Food xchegg.com/chat?fron X New tab 1538037&cmid=2403604&page=1 X dee LiveSafe M Gmail YouTube Maps STAT_101_HW1_202... Hotel Rates for Busi... Camb dia All courses Help Suppose there is a significant relationship between the course performance and attendance. Use the following Excel output and answer the following questions. SUMMARY OUTPUT Time left 0:33: Regression Statistics Multiple R 0.4051 R Square 0.1641 Adjusted R Square 0.0713 Standard Error 11.5389 Observations 11 ANOVA df SS MS F Significance F Regression 1 235.31 235.31 1.77 0.2164 Residual 9 1198.32 133.15 Total 10 1433.64 Coefficients Standard Error t Stat P-value Lower 95% Intercept 46.06 27.12 1.70 0.12 -15.29 Attendance 0.54 0.41 1.33 0.22 -0.38 a) Write the least square regression line. Please pay special symbol use. [1] b) Provide an interpretation of the slope estimate. [21 Q Search 100 & 7 8 9 0 - 6 1/2 T Y U P G H J K L
Added by Maria M.
Close
Step 1
06 and slope b1 (Attendance) = 0.54. Show more…
Show all steps
Your feedback will help us improve your experience
Banhishikha Sinha and 69 other Intro Stats / AP Statistics educators are ready to help you.
Ask a new question
Labs
Want to see this concept in action?
Explore this concept interactively to see how it behaves as you change inputs.
Key Concepts
Recommended Videos
The following Excel tables are obtained when "Score received on an exam (measured in percentage points)" (Y) is regressed on "percentage attendance" (X) for 22 students in a Statistics for Business and Economics course. Regression Statistics Multiple R: 0.142620229 R Square: 0.02034053 Standard Error: 20.25979924 Observations: 22 Coefficients | Standard Error | T Stat | P-value Intercept: 39.39027309 | 37.24347659 | 1.057642216 | 0.302826622 Attendance: 0.340583573 | 0.52852452 | 0.644404489 | 0.526635689 Question 9 (0.5 points) The following Excel tables are obtained when "Score received on an exam (measured in percentage points)" (Y) is regressed on "percentage attendance" (X) for 22 students in a Statistics for Business and Economics course. Regression Statistics Multiple R: 0.142620229 R Square: 0.02034053 Standard Error: 20.25979924 Observations: 22 Coefficients | Standard Error | T Stat | P-value Intercept: 39.39027309 | 37.24347659 | 1.057642216 | 0.302826622 Attendance: 0.340583573 | 0.52852452 | 0.644404489 | 0.526635689
Madhur L.
The American Association of Individual Investors (AAII) Online Discount Broker Survey polls members on their experiences with discount brokers. The survey members were asked to rate the quality of the speed of execution and overall satisfaction with electronic trades provided by their broker. The ratings ranged from unsatisfied (1), somewhat satisfied (2), satisfied (3), and very satisfied (4). Each broker's score was calculated by computing the weighted average of the scores provided by each respondent. Suppose a portion of the survey results follow. These ratings data were used to create a regression equation to determine the relationship between the quality of speed of execution and overall satisfaction with electronic trades. The regression equation is 0.167 + 0.9194 * X, where X represents the quality of speed of execution. The significance level for the regression equation is 0.05. State the null and alternative hypotheses: Ho: β1 = 0 Ha: β1 ≠ 0 Ho: β0 = 0 Ha: β0 ≠ 0 Set up the ANOVA table: Find the test statistic: Find the p-value:
Lucas F.
Burmer Co. has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs must be determined. Data regarding the machine hours and maintenance costs for the last year and the results of the regression analysis are as follows: Month Maintenance Cost Machine Hours Jan. $5,040 620 Feb. $3,600 420 Mar. $4,320 520 Apr. $3,380 390 May $5,220 650 June $3,550 400 July $3,640 430 Aug. $5,360 680 Sept. $5,110 640 Oct. $4,860 610 Nov. $3,960 460 Dec. $3,790 440 Sum $51,830 6,260 Average $4,319 522 A staff assistant has run regression analyses on the data and obtained the following output using Excel: REGRESSION ANALYSIS Y (Dependent) Variable: Maintenance Cost X (Independent) Variable: Maintenance Hours Regression Statistics Multiple R 0.998210294 R Square 0.996423791 Adjusted R Square 0.99606617 Standard Error 47.0629563 Observations 12 ANOVA df SS MS F Significance F Regression 1 6171342.448 6171342 2786.257 1.44166E-13 Residual 10 22149.21856 2214.922 Total 11 6193491.667 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 783.7782188 68.34114772 11.46861 4.47E-07 631.504653 936.051785 Hours 6.777102456 0.12839066 52.78501 1.44E-13 6.491030239 7.06317467 The t statistic for the independent variable: Is statistically significant at less than 5% risk At 11.46861, is statistically significant At 52.78501, is too large to be statistically significant Lies somewhere between 6.491 and 7.063
Recommended Textbooks
Elementary Statistics a Step by Step Approach
The Practice of Statistics for AP
Introductory Statistics
Watch the video solution with this free unlock.
EMAIL
PASSWORD