Q6. The outcome variable in a linear regression is best measured on which of the following scales? a. Categorical B. Continuous C. Ordinal D. None of the above
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Q: O a. None
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A: *Answer:
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- Q14. The slope for an independent variable X predicts where the regression line crosses the Y (dependent) axis. a. TrueB. FalseC. None of the aboveThe datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…Listed below are the numbers of commuters and the number of parking spaces at different Metro-North railroad stations. Use technology (calculator) to help you answer the following, and round to the 3 decimal places where rounding is necessary. . a. Find the linear regression line y = a + bx. b. Are the variables positively or negatively related? c. Find and interpret r2. Make sure to include what it means specific to this data set. d. Use your regression line to make a prediction for the number of parking spaces for a station with 900 e. Identify and interpret the slope of the linear model.
- D. Calculate a linear regression using Stabley. Write the equation below. E. What is the correlation coefficient? f. What is the slope of your LSRL? Interpret the slope using context. G. What is the Y- intercept of your LSRL? Interpret the Y-intercept using contextAutomobile racing, high-performance driving schools, and driver education programs run by automobile clubs continue to grow in popularity. All these activities require the participant to wear a helmet that is certified by the Snell Memorial Foundation, a not-for-profit organization dedicated to research, education, testing, and development of helmet safety standards. Snel| "SA" (Sports Application) rated professional helmets are designed for auto racing and provide extreme impact resistance and high fire protection. One of the key factors in selecting a helmet is weight, since lower weight helmets tend to place less stress on the neck. The following data show the weight and price for 18 SA helmets (SoloRacer website). Helmet Weight (oz) Price ($) Pyrotect Pro Airflow 64 241 Pyrotect Pro Airflow Graphics 64 276 RCi Full Face 64 202 RaceQuip RidgeLine 64 197 HJC AR-10 58 291 HJC Si-12 47 708 HJC HX-10 49 910 Impact Racing Super Sport 59 331 Zamp FSA-1 66 197 Zamp RZ-2 58 292 Zamp RZ-2…Show step by step on EXCEL. I am having a hard time on this.
- Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative? A. The slope is negative. As the independent variable increases the dependent variable also tends to increase. B. The slope is negative. As the independent variable increases the dependent variable tends to decrease. C. The slope is positive. As the independent variable increases the dependent variable also tends to increase. D. The slope is positive. As the independent variable increases the dependent variable tends to decrease.Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 88 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−0.813+0.177?,h^=−0.813+0.177w, with standard error for the coefficient of ?w equal to 0.448. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.How many independent variables are involved in a multiple regression equation? a. One b. Zero c. Two or more d. At least three
- A vocational counselor uses the number of days without employment to predict her clients' feelings of self efficacy, measured on a scale of 1 to 5, with higher numbers meaning that clients feel more secure in their job related abilities. The slope of the regression line is –1.02. Which statement is the best interpretation for this finding? a. For every 1-point increase in self-efficacy, there is an associated decrease in the number of days of unemployment. b. For every additional day of unemployment, there is an associated decrease in self-efficacy of 1.02 points. c. The least number of days a person can be unemployed and still feel self-efficacious is 3.98 points d. The decrease in self-efficacy of 1.02 points is caused by each additional day of unemploymentThe following chart shows the actual sales for the last 12 months for a given company. Assume that sales are best fit by a linear trend and you can use single linear regression to set up a forecasting model. Using the sales data answer below questions (justify your answers): A.What would be the typical linear regression equation for the number of sales? B.Make the sales forecast for period 15 of next year. C. Make the sales forecast for period 17 of next year. D. What is the standard error for the data?a. What is a residual? b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? a. What is a residual? OA. Aresidual is a point that has a strong effect on the regression equation. OB. A residual is the amount that one variable changes when the other variable changes by exactly one unit. OC. Aresidual is a value that is determined exactly, without any error. OD. Aresidual is a value of y - y, which is the difference betvween an observed value of y and a predicted value of y. b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? The regression line has the property that the of the residuals is the possible sum.