SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R Square0.9590.9190.909Standard Error3.756Observations10.000ANOVAdfSSMSSignificance F1.0001,285.245RegressionResidual1,285.24591.1050.0008.000112.85814.107Total9.0001,398.103t StatP-valueLower 95% Upper 95% Lower 95.0% Upper 95.0%(1.591)Coefficients itandard ErroiIntercept7.9954.1571.9230.09117.581(1.591)17.581Years in College12.6751.3289.5450.0009.61315.7379.61315.737a) Which variable is the dependent variable? Which is the independent variable?For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac).BIUSParagraphArial10ptI!!! The following sample data contains the number of years of college and the current annual salary for a random sample of heavy equipment salespeople. A researcher believes that spending more years in collegeleads to higher annual income. (80 points)Annual IncomeYears in College(In Thousands)31.2235.9239.054.6443.7328.157.7446.862.44.60.84SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R Square0.9590.9190.909Standard Error3.756Observations10.000

The equation of the line is given by,

Answered: SUMMARY OUTPUT Regression Statistics…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Source df SS MS Group 4 42.272 10.568 4.3627 Error 20 48.446 2.4223 Total 24 90.718 a. At 0.05 significance, what is the value of the test statistic F? (use 5 decimal places) www b. Should Ho be rejected according to the ANOVA table? (YES or NO)
Group 2 wieght gender 2. 37 2. 2 37 37 40 2. 2 2 40 40 43 gender Group 1 wieght 50 45 45 45 1 50 55 2. 2 46 47 1 58 60 60 47 48 2 2 48 48 1 1 62 49 50 50 1 68 2 68 69 69 1 2. 53 5B 2 58 60 60 70 Median Mode: Mean S Varinace Std. dev Median Mode: Mean Varinace Sd dev Sid Error. Std Error.
O E QUESTION 37 When conducting a one-way ANOVA, the compared to the within-treatment variability, the the between-treatment variability is when the value of F will be tend to be. smaller, larger smaller, smaller larger, larger smaller, more random larger, more random a. b. C. d. e. OA OB . OD QUESTION 38
Please help me to interpret all the value.
A regression analysis was performed and the summary output is shown below. Regression Statistics Multiple R 0.7802268560.780226856 R Square 0.6087539470.608753947 Adjusted R Square 0.5870180550.587018055 Standard Error 6.7217061336.721706133 Observations 2020 ANOVA dfdf SSSS MSMS F� Significance F� Regression 11 1265.3871265.387 1265.3871265.387 28.006928.0069 4.9549E-054.9549E-05 Residual 1818 813.264813.264 45.18145.181 Total 1919 2078.6512078.651 Step 1 of 2: How many independent variables are included in the regression model
Analysis of Variance results: Where: Age > 5Responses: AgeFactors: Sex Response statistics by factor Sex n Mean Std. Dev. Std. Error female 121 10.490083 4.2222704 0.38384277 male 155 9.0806452 3.0091656 0.241702 ANOVA table Source DF SS MS F-Stat P-value Sex 1 134.98939 134.98939 10.466692 0.0014 Error 274 3533.79 12.897044 Total 275 3668.7794 Tukey HSD results (95% level) female subtracted from Difference Lower Upper P-value male -1.4094375 -2.2670907 -0.55178425 0.0014 In one complete sentence, interpret your confidence interval. Make sure in the interpretation it is clear the direction of the difference (i.e. which gender weighs more and by how much. Explain why a confidence interval provides more information to a tiger researcher than the results of a hypothesis test
What percentage of the variability in the number of delivery days for a car is NOT explained by knowing the number of factory options? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Intercept Factory Options 22.31% 72.16% 88.14% 77.69% O 4.64% 0.8814 0.7769 0.7216 4.6400 10 Coefficients 29.73333 3.284848 Standard Error 2.991435587 0.482113498
3.Which model do you think is the “best” reduced model? Discuss why you choose this model. Analysis of Variance Table (Step back model) Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 17.1136 0.0003079 *** sqft 1 35364 35364 28.8196 1.134e-05 *** sd 1 5961 5961 4.8576 0.0362339 * unts 1 8678 8678 7.0722 0.0130049 * gar 1 33364 33364 27.1899 1.713e-05 *** cp 1 7641 7641 6.2269 0.0189934 * Residuals 27 33131 1227 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Step forward model: Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 16.6255 0.000406 *** sqft 1 35364 35364 27.9976 1.757e-05 *** sd 1 5961 5961 4.7191 0.039517 * unts 1 8678 8678 6.8705 0.014697 * gar 1 33364 33364 26.4144 2.599e-05 *** cp 1 7641 7641 6.0493 0.021176 *…
2. CREATININE LEVEL PROBLEM Some statistics Analyzer A: mean = 105.75; median = 99.5 Analyzer B: mean = 97.5; median = 89.5 Let difference = Analyzer A - Analyzer B d=8.25 Md = 7 data: Analyzer A W = 0.88028 p-value = 0.1895 Wilk-Shapiro Test for Normality data: Analyzer B W = 0.91541 p-value = 0.3937 Ha: not equal to 0 t = 2.9652 p-value = 0.02095 data: difference W = 0.95788 p-value 0.7897 Student's t-test on Paired Samples: Analyzer A vs Analyzer B Ha: less than 0 t = 2.9652 p-value = 0.9895 Ha: greater than 0 t = 2.9652 p-value = 0.01048 Wilcoxon Matched-Pairs Signed Ranks Test: Analyzer A vs Analyzer B Ha: not equal to 0 Ha: less than 0 Ha: greater than 0 V = 27 V = 27 V = 27 p-value = 0.03461 p-value = 0.9888 p-value 0.01731 F-test for Equality of Variances F = 1.1311 p-value = 0.856 Student's t-test on Two Independent Pop'n Means: Analyzer A vs Analyzer B Ha: not equal to 0 Ha: less than 0. Ha: greater than 0 t = 9.2109 t = 9.2109 t = 9.2109 p-value 0.00003668 p-value=1 p-value…
Salary information regarding male and female employees of a large company is shown below. Male Female Sample Size 68 34 Sample Mean Salary 46 43 (in $1,000s) Population Variance (o2) 136 68 The standard error is 2. What is the margin of error at 95% confidence? 1.960 3.920 3.960 7.840
WALKING RUNNING Mean 7.181818182 7.3636364 Variance 4.563636364 6.4545455 Observations 11 11 Pooled Variance 5.509090909 Hypothesized Mean Difference 0 df 20 t Stat -0.181668105 P(T<=t) one-tail 0.428835886 t Critical one-tail 1.724718243 P(T<=t) two-tail 0.857671772 t Critical two-tail 2.085963447 If the t-Stat value is less than the t Critical two-tail value I can reject the null, right? I am still a little confused on what a few numbers represent.
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