The following table indicates the ages of a sample of female employees of People Plus Pty, and the corresponding monthly income of each employee (in thousa
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The following table indicates the ages of a sample of female employees of People Plus Pty, and the corresponding monthly income of each employee (in thousands of Rands).
Age In Years (x) 40
49
32
27
38
46
Monthly Income (R000s) (y) 43
49
36
31
41
42
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By completing the table given below, and then applying the relevant formulae, determine the linear regression
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If a female employee is 39 years of age, estimate her monthly income.
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- The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 7171 6262 7878 9494 8383 8181 8080 9494 8585 6262 Grades on Final 8888 7979 8888 9191 8080 7070 7171 9393 6565 7777A researcher wants to investigate the influence of the average no. of nights spent per year by the tourists from Japan on the average amount spent by them. Table 3 shows the related data obtained from the Department of Statistics Malaysia website. Table 4 shows a portion of Microsoft Excel output for the regression analysis performed based on the data in Table 3. Table 3: Data on the nights spent by tourists from Japan and amount spent Year Average no. of nights spent Average amount spent (in RM billion) 2010 5.9 1.1 2011 6.1 1.1 2012 6.1 1.4 2013 6.3 1.5 2014 6.4 1.8 2015 6.1 1.6 2016 6.2 1.3 2017 6.3 1.2 2018 6.6 1.7 2019 6.9 2.3 Table 4: Regression analysis Coefficients Standard Error t Stat P-value Intercept B0 1.4555 -3.7583 0.0056 Average no. of nights spent B1 0.2312 4.7934 0.0014 a. Note that the value of B0 and B1 are missing from Table 4.…3. (a). Differentiate the different types of linear regression and describe the use of regression in geographical study. (b). Calculate the value of the slope, b, for observations of n = 22, r2 = 0.73, standard deviation of x = 2.3 and the regression sum of square = 1324.
- For10 observations on supply (X) and price (Y) the following data are obtained: ∑X=130, ∑X2=2280, ∑Y2=5506 , ∑XY=3467, ∑Y=220 Obtain regression line Y on X and estimate supply when price is 16.Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)The monthly premium quoted by an insurance company for a critical illness policy was collected from a sample of 6 adult male smokers at different age. The data for the sample are shown: Age 28 25 50 39 47 31 Premium ($) 75 40 175 125 250 105 Using Age to predict premium, the Linear Regression equation is given by: ŷ =6.556X−112 and r2=0.813y^=6.556X−112 and r2=0.813 a. Identify the independent and Dependent variables. Dependent: Age Premium Independent: Age Premium b. Determine the slope. Slope = Slope = Round to 3 decimal places c. Determine |r||r| . |r|=|r|= Round to 3 decimal places d. Interpret rr : and e. Determine critical r value at 5% significance level and determine if there is a significant linear correlation exists. |r| critical=|r| critical= Round to 3 decimal places Linear Correlation:Linear Correlation: Significant Not Significant f. Predict the monthly premium for a 40 years old adult male smoker.…
- 10. You estimated a regression with the following output. Source | SS df MS Number of obs = 333 -------------+---------------------------------- F(1, 331) = 4608.21 Model | 32636494.1 1 32636494.1 Prob > F = 0.0000 Residual | 2344225.8 331 7082.25316 R-squared = 0.9330 -------------+---------------------------------- Adj R-squared = 0.9328 Total | 34980719.9 332 105363.614 Root MSE = 84.156 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 30.79902 .4537022 67.88 0.000 29.90652 31.69153 _cons | 20.85313 42.1964 0.49 0.621 -62.1538 103.8601…The table below shows a set of four regression results of the effect of student-teacher ratio on average test score. Note each column represents the estimates related to each regression. The numbers in parenthesis below the coeffcients are the standard errors. Also, assume all the variables are continuous. (3) Regressor Student-teacher ratio (STR) (1) (2) (4) -1.00 -0.890 -0.757 -0.967 (0.27) (0.23) (0.31) (0.24) STR^2 0.865 0.875 (0.24) (0.29) % English Leamers (EL) -0.122 -0.112 -0.095 -0.067 (0.033) (0.054) (0.036) (0.057) STR x EL -0.098 -0.09 36.89 (0.033) (0.023) (9.31) STR^2 x EL 34.7 (5.60) Intercept 700.2 700.4 659.6 870.2 (5.60) (5.70) (4.60) (4.30) Standard Error of the Regression (SER) 9.08 (Adjusted) R-Squared Number of Observations 9.09 8.64 8.57 0.473 0.478 0.594 0.892 420 420 420 420 Based on the results of this table, which of the following statements best describes how the results should be interpreted (consider only individual effects on joint effects)? Oa There are…This table reports the regression coefficients when the returns of the size-institutionalownership portfolio (columns 1 and 2) returns are regressed on three variables: a constant(column 3), the stock market returns (column 4), and the change of the value weighted discountof the closed end fund industry (column 6). Columns 5 and 7 report the corresponding t-statistics of the coefficient estimates. Note that a t-statistic with an absolute value above 1.96means the coefficient estimate is significantly different from 0 at the 1% level. Column 8reports the R square of the regressions. Column 9 reports the mean institutional ownership ofeach portfolio. The last column reports the F-statistics for a multivariate test of the null hypothesis that the coefficient on ΔVWD in the Low (L) ownership portfolio is equal to theHigh (H) ownership portfolio. Two-tailed p-values are in parentheses. 1. What is the main finding of this Table? 2. What is the explanation for…
- The grades of a class of 9 students on a midterm report (x) and on the final examination (y) are as follows: Give the following: a. linear regression line and equation b. computation of the coefficient of determination ?^2 c. Computation of the coefficient of correlation ? d. Estimate the final examination grade of a student who received a grade of 85 on the midterm report.For each gender, estimate an earnings regression where the dependent variable is Annual Earnings and the independent variable is Age. Report the results for each regression, and provide an interpretation of the coefficient associated with age. Female- annual earning: 49347.58 age: 42.81 education: 14.4 Male- Annual earning: 69984.54 age: 42.86 education: 14.11.One set of 20 pairs of scores, X and Y values, produces a correlation of r = 0.70. If SSY = 150, calculate the standard error of the estimate for the regression line