Current Attempt in Progress Test the slope of the regression line, -15.63 -0.711 x of the following data. Use a 5% level of significance and s₂ = 3.097. Bond Rate Prime Interest Rate 5% 17% 11 6 9 8 17 3 7 7 (Round the intermediate values to 5 decimal places. Round your answer to 2 decimal places) Observed t = The decision is to reject the null hypothesis eTextbook an fail to reject the null hypothesis
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- Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyBrain size Does your IQ depend on the size of yourbrain? A group of female college students took a test thatmeasured their verbal IQs and also underwent an MRI scan to measure the size of their brains (in 1000s of pix-els). The scatterplot and regression analysis are shown, and the assumptions for inference were satisfied.Dependent variable is: IQ_VerbalR-squared = 6.5% s = 21.5291 df = 18Variable Coefficient SE(Coeff)Intercept 24.1835 76.38Size 0.098842 0.0884a) Test an appropriate hypothesis about the associationbetween brain size and IQ.b) State your conclusion about the strength of thisassociation.
- ABC University uses data from a random sample of students in a regression analysis to see i he number of hours a student spends playing video games weekly (x) is a predictor of the student's GPA (y) at the end of the term. An intern for ABC goes ahead and performs the regression using Excel. Examine the following Excel regression printout. Describe what the value -0.0292...in the cell next to "X Variable 1" label means. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.709640286 0.503589336 0.45394827 Standard Error 0.552383099 Observations 12 ANOVA df SS MS Regression 3.095395785 3.09539579 28 72.28745 Residual 10 3.051270881 0.3051270937 Total 11 6.146666667 Coefficients Standard Error t Stat P-value Interce pt X Variable 1 3.46198431 0.296274535 11.6850552 11 1.94E-10 -0.029275496 0.009191503 -3.1850607 37 6.88E-06 Regression should not be used on the data set. The correlation coefficient is -0.0292 when rounded to 3 places. The regression line has a…The coefficient of correlation in a simple regression analysis is = -0.6. The coefficient of determination for this regression would be 0.36 - 0.36 0.6 0.13 O 0.6 or + 0.6Given the correlation coefficient -0.994 and the linear regression equation = 212-1.81x, compute the coefficient of determination. ² Round to 4 decimal places. Search SAMSUNG SUBMIT QUESTION HE W SAVE PROGRESS SUBMIT A
- A statistics student wanted to determine if the distance to a destination was related to the price an airline would charge to fly to that destination. The student did a regression of airfare, y, on distance, x, and obtained the printout shown below from a statistical software package. Predictor Coef Constant 83.02 Distance 0.117 Oŷ= 0.117+83.02x Oy=83.02 +0.117x Oy= 49.29 + 83.02x Oŷ= 0.028 + 0.117x Oy=83.02 + 25.25x 1 SE Coef 49.29 0.028 S = 25.25 R-Sq = 63.2 % Which of the following is the correct equation of the least-squares line? Mark this and return t-ratio 1.689 4.179 R-Sq (Adj) = 64.7% Save and Exit р 0.046 0.000 di I tv Next AM Submit AaWhich of the following is not a plot of residuals typically used in multiple regression analysis?Select one:a. None of these b. Residuals versus correlation coefficients..c. Residuals versus X1.d. Residuals versus timee. Residuals versus X2.please do all parts! The estimated regression equation for this data set is y=4.4878+1.9549x. Part A: (in image) Part B: is the linear function is the appropriate regression function for this data set? Part C: do the residuals have a constant variance? Part D: are the residuals independent? Part E: are the error terms are normally distributed? y x22 821 818 846 2241 2254 2276 3258 3268 32
- The service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression shown below. Table 7: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .854a .730 .695 6.6235 a. Predictors: (Constant), Hourly Wage Table 8: ANOVA ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1918.458 1 1918.458 129.783 .000a Residual 709.567 48 14.782 Total 2628.025 49 a. Predictors: (Constant), Hourly Wage b. Dependent Variable: Number of Complaints Table 9: Coefficients Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 20.2 4.357 4.636 .000 Hourly Wage -1.20 .088 -.946 -13.636 .000 a. Dependent Variable: Number of…The service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression shown below. Table 7: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .854a .730 .695 6.6235 a. Predictors: (Constant), Hourly Wage Table 8: ANOVA ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1918.458 1 1918.458 129.783 .000a Residual 709.567 48 14.782 Total 2628.025 49 a. Predictors: (Constant), Hourly Wage b. Dependent Variable: Number of Complaints Table 9: Coefficients Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 20.2 4.357 4.636 .000 Hourly Wage -1.20 .088 -.946 -13.636 .000 a. Dependent Variable: Number of…Q1: Use regression to analyze the data below. GDP Growth is your dependent variable and Jobles Claims is your indepdendent variable. Year GDP Growth (%) Jobs_Created 2019 2.33% 88000 2018 3.18% -160000 2017 2.22% -213000 2016 1.57% -147000 2015 2.88% -215000 2014 2.45% -385000 2013 1.84% -320000 2012 2.25% -439000 2011 1.55% -522000 2010 2.56% -899000 2009 -2.54% 308000 2008 -0.14% 1919000 2007 1.88% 305000 2006 2.86% -205000 2005 3.51% -111000 2004 3.80% -487000 2003 2.86% -204000 2002…
