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- A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x= 3.3333, s= 2.5033, y = 4.0667, s, = 1.9449, and r= - 0.9585, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 3 4 5.8 6.3 5.1 3.4 1.8 2.0 重 (a) Choose the correct graph below. OA. O B. OD. 本y 7- Ay 本y 7- AY 7- 0- 0. 0- 0. 6. There appears to be relationship. (b) ŷ =[]x+ (D (Round to three decimal places as needed.) (c) Choose the correct graph below. O A. О В. OC. O D. Ay 7- Ay 7- 0- 0. 9. 6. O Time Remaining: D TCOA2334403 U 10-8-2014 MAIN TCOA2330401 (2) Q 出4. The following information was taken from a computer printout generated from least squares regression analysis for use in estimating overhead costs: Coefficient 25 2,700 Standard Error value 18 67.33 2.14 5.08 Slope Intercept Summary Statistics Correlation coefficient Coefficient of det ermination Standard error Observations Anova F value Significance of F 72 5184 137.03 10 42.5 .045 Predict the overhead cost for 200X. a. $2,700 b. $7,700 c. $3,697.33 d. $5,000A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x= 3.6667, sy = 2.2509, y= 3.6833, s, = 1.8809, and r= - 0.9511, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 1 4 4 6 6 y 5.0 6.3 4.2 3.4 1.4 1.8 (a) Choose the correct graph below. OA. B. OC. OD. Ay 74 Ay Ay 7- .. .. There appears to be a linear, negative relationship. (b) y=x+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A. B. OC. D. Ay 0-
- 2.1. Give one word for the following statements or scenarios: 2.1.1. The data collected by the researcher from the Department of Education were the 2020 matric results for all South African high schools in disadvantaged areas.. 2.1.2. This analysis can be performed using either the method of moving averages, or by fitting a straight line using the method of least squares from regression analysis.99. What is the least squares regression line for the following scatter plot? y-hat =-0.34x + 3.78 y-hat = -0.42x + 4.12 y-hat = -0.31x + 3.09 y-hat = -0.39x + 4.304. We would like to determine how a man's weight can be used to predict his systolic blood pressure. We measure the weights (in pounds) and the systolic blood pressures of a sample of 17 men. The data are plotted on a scatterplot and it can be seen that a linear relationship is a reasonable assumption. The least squares regression line is calculated to be ŷ = 125.561 + 0.145x. The ANOVA table (with some values missing) is shown below: |Source of Variation | df | Sum of Squares Mean Square F Regression Error Total 26.46 617.82 (a) We would like to test whether a linear relationship exists between a man's weight and his systolic blood pressure. We will conduct an analysis of variance to test Ho: B1 = 0 vs. Ha: B1 + 0 at the 5% level of significance. Enter all missing values in the ANOVA table. Calculate the value of the test statistic, find the P-value of the test and provide a properly worded conclusion. (b) What is the value of the correlation between weight and systolic blood pressure…
- Add to MyRegistry 9 Mail - sgorham@a.. Like father, like son: In 1906, the statistician Karl Pearson measured the heights of 1078 pairs of fathers and sons. The following table presents a sample of 6 pairs, with height measured in inches, simulated from the distribution specified by Pearson. Compute the least-squares regression line for predicting son's height (v) from father's height (x). Round the slope and y-intercept values to at least four decimal places. Father's Son's height height 73.6 74.9 66.7 68.8 70.1 73.3 72.3 71.9 73.6 76.5 69.3 71.4 Send data to Excel Regression line equation: Save For Later Submit Assignment Check Answer © 2021 McGraw Hill LLC. AlI Rights Reserved. Terms of Use Privacy CenterPlease send me the question in 30 minutes it's very urgent plzSuppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. Thecorrelation coefficient is 0.944 and the least squares regression line is y = 0.199x + 11.982. Complete parts (a) and (b)below.Height, x27.5 25.5 26.25 25.25 27.5 26.25 26 27.25 27.25 27 27.25 ФHead Circumference, # 17.5 17.0 17.2 17.0 17.5 17.3 17.2 17.4 17.3 17.3 17.4(a) Compute the coefficient of determination, R?R?.% (Round to one decimal place as needed.)(b) Interpret the coefficient of determination and comment on the adequacy of the linear model.Approximately % of the variation inis explained by the least-squares regression model.According to the residual plot, the linear model appears to be (Round to one decimal place as needed.)
- 16. A scatterplot of the monthly salary (in thousands of pesos) versus years of education for seven full-time workers is displayed below. The least- squares regression line is drawn on the plot. Six of the data points are plotted with open circles and the seventh is plotted with a solid circle. The data point plotted with a solid circle to 20 Ne stynan eftdutatien A. has a large residual and is influential. B. has a small residual and is influential. C. has a large residual and is not infiluential. D. has a small residual and is not influential. 00 09 oad jo umroy sA data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x = 3.6667, sx =2.4221, y = 3.8667, sy = 1.8435, andr= -0.9525, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). D O A. (a) Choose the correct graph below. Ay 6- X y 0 0 2 3 5 6 6 5.8 5.7 5.0 2.8 1.7 2.2 O G B. Ay 6- Q (...) C. 0- ● Q D. Ау 0- X 6Question 5 of 19 Compute the MSE for the following data. Period 1 2 3 4 5 6 13 Select the correct response. 12 11 Actual 492 470 485 493 498 492 14 Forecast (Error) 495 465 487 490 499 498 -5 -3 1 6 |Error] 3 LO 5 2 3 1 6 Error² 9 25 4 9 1 36 Error/Actual*100 0.60 1.06 0.41 0.60 0.20 1.21
