ayu órmulas Data Review View Tell me what you want to do Conditional FormattingInsert Format as Table V Cell Styles v General Delete Sort & Format v × v Filter AC AD AE Logins Age HBA1C Please copy the charts/tables below 0 69.9 16 36.8 28 7.8 6.8 6 5.7 60.314.9 6.8 7.5 6.9 70.1 6.7 5.8 5.3 39 SUMMARY OUTPUT 73.3 65.4 10 66.6 Regression Statistics Multiple R R Square Adjusted R 5quare Standard Error Observations 0.193094044 0.03728531 0.037096635 392627995 56.7 59.2 1 47.4 0.7 9.4 ANOVA 56.4 5.6 2 766.5198577 383.2599289 197.6164858 70 9.5 Regression Residual Total 0 Reject HO 16 64 6.4 55.7 61 54.85.8 10205 19791 70694 1.939412733 10207 20558.2268 63 Coefficients Standard Error t Stat Lower 95% Upper 95% 8.763176193 0.083831476 104 5332452 0.008618613 0.001023635 8 4142073 4.284481-17 0.010 0.025215089 0.001343904-18.762561553.0239E-77 0 8.59885003 8.927502356 1153.963 Intercept X Variable 1 X Variable 2 37.6 54.97.5 56.5 58.2 57.2 49.3 9.98.2 46.8 52.3 Tap: (0106, 0066) baseline: (0278, 0225) HbA1C- 8.76-0086 logins-.025 age 44
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Based on this table: 1) What is the p-value for the overall regression test? 2) What is the ...
1.Based on the table above, how to intepret this regression analysis? 2. When we need to...
1.Based on the table above, how to intepret this regression
analysis?
2. When we need to look at the adjusted r2 and why?
3. How to conduct the hypothesis test?
0 Regression Statistics 1 Multiple R 2 R Square 3 Adjusted RS 0.853658537 0,97530483 0.951219512 4 Standard Err 0.191273014 5 Observation 6 7 ANOVA Significance F 0.220863052 df SS MS 0.713414634 0.356707 9 Regression 0 Residual 1 Total 2. 9.75 1 0.036585366 0.036585 0.75 2 Lower 95 % 3 Coefficients...
From the regression example discussed in class and based on the information below: Regression Statistics Multiple...
From the regression example discussed in class and based on the information below: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.925 0.856 0.846 0.059 45 ANOVA P dfss SMS 3 0 .85 0.14 440.99 Significance F 0.00 Regression Residual Total 0.28 0.00 81.46 Intercept PRICE INCOME WEATHER Coefficients 13.040 -0.200 1.500 0.124 Standard Error 0.758 0.063 0.079 0.065 Stat P-value 17.1940 .000 -7.904 0.000 13.162 0.000 1.909 0.063 L ower 95% 11.508 -0.627 0.883 -0.007...
In relation to the below output from the Regression Analysis of the S&P/ASX200 Index (X) and...
In relation to the below output from the Regression Analysis of the S&P/ASX200 Index (X) and from the company ABC Shares derived from weekly data over a 12 month period, can you please explain the key measures and what this all means eg. Number of Observations, R Square, Value of the Slope and the P-Value of the Slope etc. SUMMARY OUTPUT Regression Statistics Multiple R 0.045274332 R Square 0.002049765 Adjusted R Square -0.01790924 Standard Error 0.023996449 Observations 52 ANOVA df...
Step 1 For each of the independent variables contained in the regression model in Step 1, test their statistical signif...
Step 1
For each of the independent variables contained in the
regression model in Step 1, test their statistical significance.
In testing statistical significance of a regression
coefficient, you have to justify your choice of one or two tail
test. (PLEASE SHOW ALL WORKING)
SUMMARY OUTPUT Regression Statistics Multiple R 0.31179522 0.097216259 R Square Adjusted R Square0.08877902 Standard Error 15.42093465 Observations 649 ANOVA df MS Significance F Regression 6 16440.370442740.0617411.52229408 2.87685E-12 Residual 642 152670.9547 237.8052254 Total 648 169111.3251 P-value Coefficients...
What percent of the variance in well production is explained by knowing well depth and well...
What percent of the variance in well production is explained by knowing well depth and well age? SUMMARY OUTPUT Regression Statistics Multiple R 0.98711 R Square 0.974387 Adjusted R Square 0.965849 Standard Error 47.4523 Observations 9 ANOVA df SS MS F Significance F Regression 2 513960.7 256980.4 114.1262 1.68E-05 Residual 6 13510.32 2251.72 Total 8 527471.1 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -100.805 48.43281 -2.08133 0.082583 -219.316 17.70612 -219.316 17.70612 Well...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45 6 Anova df SS MS F Significance F 0.11 1 41497.60 41497.60 4.20 Regression Residual 4 39561.23 9890.31 Total 5 81058.83 t Stat P-value Coefficients Standard Error 1423.60 564.95 2.52 0.07 Intercept X Variable 1 Lower 95% Upper 95% -144.96 2992.16 -0.11 0.72 Lower 95.0% Upper 95.0% -144.96 2992.16 -0.11 0.72 0.31 0.15 2.05 0.11 Assume that Craig's Fresh and Hot Pancake Restaurant does...
Regression Statistics Multiple R 0.896755 R Square 0.80417 Adjusted R Square 0.767452 Standard Error 51.04855 Observations...
Regression Statistics Multiple R 0.896755 R Square 0.80417 Adjusted R Square 0.767452 Standard Error 51.04855 Observations 20 ANOVA df SS MS F Significance F Regression 3 171220.5 57073.49 21.90118 6.56E-06 Residual 16 41695.28 2605.955 Total 19 212915.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 427.1938 59.60143 7.167509 2.24E-06 300.8444 553.5432 300.8444 553.5432 Temp (deg) -4.58266 0.772319 -5.93364 2.1E-05 -6.21991 -2.94542 -6.21991 -2.94542 Insulation (ins.) -14.8309 4.754412 -3.11939 0.006606 -24.9098 -4.75196 -24.9098 -4.75196...
7,10,11 Based on the following regression output, what is the equation of the regression line? Regression...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
Consider the excel regression above. What null hypothesis is the (default) F-test, which is reported on the results, testing? What is the calculated F-statistic value and what is the p-value of the te...
Consider the excel regression
above. What null hypothesis is the (default) F-test, which is
reported on the results, testing? What is the calculated
F-statistic value and what is the p-value of the test? How many
numerator degrees of freedom (restrictions) are involved?
Regression Statistics MultipleR 0.267643168 0.071632865 R Square Adj R Square 0.068838449 Standard Error571.4177199 Observations 3000 ANOVA df Significance F MS 9 75330553.98 8370061.553 25.634287096.23834E-43 Regression Residual 2990976289449.8 326518.2106 Total 2999 1051620004 Coefficients Standard ErrortStat P-value Lower 95% Upper...
g. Use MS Excel Data Analysis ToolPak to perform a multiple regression analysis using Quality as...
g. Use MS Excel Data Analysis ToolPak to perform a multiple regression analysis using Quality as the response variable and Helpfulness, Clarity, Easiness, and raterInterest as the explanatory variables. Write down the resulting regression equation and provide the regression output. h. Based on the regression output in part g), which variable(s) seem to be significant predictors of Quality? Which variable(s) do you suggest removing from the model in part g)? Explain why. Regression Statistics ANOVA Multiple R 0.998557685 df SS...
1.Based on the table above, how to intepret this regression
analysis?
2. When we need to look at the adjusted r2 and why?
3. How to conduct the hypothesis test?
0 Regression Statistics 1 Multiple R 2 R Square 3 Adjusted RS 0.853658537 0,97530483 0.951219512 4 Standard Err 0.191273014 5 Observation 6 7 ANOVA Significance F 0.220863052 df SS MS 0.713414634 0.356707 9 Regression 0 Residual 1 Total 2. 9.75 1 0.036585366 0.036585 0.75 2 Lower 95 % 3 Coefficients...
From the regression example discussed in class and based on the information below: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.925 0.856 0.846 0.059 45 ANOVA P dfss SMS 3 0 .85 0.14 440.99 Significance F 0.00 Regression Residual Total 0.28 0.00 81.46 Intercept PRICE INCOME WEATHER Coefficients 13.040 -0.200 1.500 0.124 Standard Error 0.758 0.063 0.079 0.065 Stat P-value 17.1940 .000 -7.904 0.000 13.162 0.000 1.909 0.063 L ower 95% 11.508 -0.627 0.883 -0.007...
Step 1
For each of the independent variables contained in the
regression model in Step 1, test their statistical significance.
In testing statistical significance of a regression
coefficient, you have to justify your choice of one or two tail
test. (PLEASE SHOW ALL WORKING)
SUMMARY OUTPUT Regression Statistics Multiple R 0.31179522 0.097216259 R Square Adjusted R Square0.08877902 Standard Error 15.42093465 Observations 649 ANOVA df MS Significance F Regression 6 16440.370442740.0617411.52229408 2.87685E-12 Residual 642 152670.9547 237.8052254 Total 648 169111.3251 P-value Coefficients...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45 6 Anova df SS MS F Significance F 0.11 1 41497.60 41497.60 4.20 Regression Residual 4 39561.23 9890.31 Total 5 81058.83 t Stat P-value Coefficients Standard Error 1423.60 564.95 2.52 0.07 Intercept X Variable 1 Lower 95% Upper 95% -144.96 2992.16 -0.11 0.72 Lower 95.0% Upper 95.0% -144.96 2992.16 -0.11 0.72 0.31 0.15 2.05 0.11 Assume that Craig's Fresh and Hot Pancake Restaurant does...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
Consider the excel regression
above. What null hypothesis is the (default) F-test, which is
reported on the results, testing? What is the calculated
F-statistic value and what is the p-value of the test? How many
numerator degrees of freedom (restrictions) are involved?
Regression Statistics MultipleR 0.267643168 0.071632865 R Square Adj R Square 0.068838449 Standard Error571.4177199 Observations 3000 ANOVA df Significance F MS 9 75330553.98 8370061.553 25.634287096.23834E-43 Regression Residual 2990976289449.8 326518.2106 Total 2999 1051620004 Coefficients Standard ErrortStat P-value Lower 95% Upper...
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