The results of a sample of 7 data points are presented below in terms of the Average Daily Temperature (oF) and the Average Monthly Precipitation (inches): Average Daily temperature x 86 81 83 89 80 74 64 Average Monthly Precipitation y 3.4 1.8 3.5 3.6 3.7 1.5 0.2 a- Draw a scatter plot b- Compute the correlation coefficient c- State the hypothesis and test the correlation significance at a = 0.0

The results of a sample of 7 data points are presented below in terms of the Average Daily Temperature (oF) and the Average Monthly Precipitation (inches): Average Daily temperature x 86 81 83 89 80 74 64 Average Monthly Precipitation y 3.4 1.8 3.5 3.6 3.7 1.5 0.2 a- Draw a scatter plot b- Compute the correlation coefficient c- State the hypothesis and test the correlation significance at a = 0.0

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.5: Correlation And Causation

Problem 2AGP

See similar textbooks

Similar questions

Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
In a study of the performance of a new engine design, the weight of 12 cars (in pounds) and the top speed (in mph) were recorded. A regression line was generated and shown to be an appropriate description of the relationship. The results of the regression analysis are below. Depend Variable: Top Speed Variable Constant Coefficient 107.58 s.e. of Coeff t-ratio prob Weight 0.8710 11.12 0.4146 9.67 0.000 2.10 0.062 R squared = 30.6% R squared (adjusted) = 23.7% s = 10.42 with 12-2 = 10 degrees of freedom Part A: Provide the regression equation based off the analysis provided & explain it in context. Part B: List the conditions for inference that need to be verified. Assuming these conditions have been met, does the data provide convincing evidence of a relationship between weight and top speed? Part C: Assuming all conditions for inference have been verified, determine a 95% confidence interval estimate for the slope of the regression line.
In the simple linear regression Y = 20 - 5X, if the coefficient of determination is 0.8, then the sample correlation coefficient is Select one: O a. 0.89 Ob. 0.64 OC. -0.89 Od. -0.64 Next page
The sample statistics for this dataset are:Height: X-bar= 67.9931 Sx= 1.90168 Weight: Y-bar: 127.0794 sy: 11.66090 Linear correlation coefficient: 0.502859 Determine the regression line and use it to predict the weight (in pounds) of a child who is 72.50 inches tall. Round you answer to two digits after the decimal point.
The coefficient of determination of a set of data points is 0.837 and the slope of the regression line is 3.26. Determine the linear correlation coefficient of the data. What is the linear correlation coefficient? (Round to three decimal places as needed.)
The regional transit authority for a major metropolitan area wants to determine whetherthere is a relationship between the age of a bus and the annual maintenance cost. A sampleof ten buses resulted in the following data: a. Develop a scatter chart for these data. What does the scatter chart indicate about therelationship between age of a bus and the annual maintenance cost?b. Use the data to develop an estimated regression equation that could be used to predictthe annual maintenance cost given the age of the bus. What is the estimated regressionmodel?c. Test whether each of the regression parameters b0 and b1 is equal to zero at a 0.05level of significance. What are the correct interpretations of the estimated regressionparameters? Are these interpretations reasonable?d. How much of the variation in the sample values of annual maintenance cost does themodel you estimated in part b explain?e. What do you predict the annual maintenance cost to be for a 3.5-year-old bus?
LINEAR REGRESSION AND CORRELATION
Report the correlations between the three independent variables (age, educ and Protestant) and your dependent variable (childs). Which category had the correlation that was the weakest?
The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 Based on the multiple regression output, if GPA and civil service ratings are held fixed, how much is the expected increase in the starting salary (pesos) for every one year increase in the years of experience?
A student collected concentration versus absorbance data for a series of standards and produced a standard curve. Which value of 2 would reflect the linear regression curve the student produced? Absorbance 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 ² = 0.10 ² = 0.76 ² = 0.98 2 = 0.45 1 Absorbance vs. Concentration 2 3 Concentration (ppm) 4 5 6
estion 3 of 38 university and gathers their freshman year GPA data and the high school SAI score reported on each of their college applications. He produces a scatterplot with SAT scores on the horizontal axis and GPA on the vertical axis. The data has a linear correlation coefficient of 0.506701. Additional sample statistics are summarized in the table below. Variable Sample Sample standard Variable description mean deviation high school SAT score x 1504.291401 Sx = 105.782904 %3D y freshman year GPA y = 3.240805 Sy = 0.441205 r = 0.506701 slope 0.002113 Determine the y-intercept, a, of the least-squares regression line for this data. Give your answer precise to at least four decimal places. tems of use Thelp about us குசங் careers 2:30 PM 10/24/20 o耳国 @ hp
Use the shoe print lengths and heights shown below to find the regression equation, letting shoe print lengths be the predictor (x) variable. Then find the best predicted height of a male who has a shoe print length of 28.5 cm. Would the result be helpful to police crime scene investigators in trying to describe the male? Use a significance level of α=0.05. Shoe Print (cm) 29.1 29.1 31.8 31.9 27.5 Foot Length (cm) 25.7 25.4 27.9 26.7 25.1 Height (cm) 175.4 177.8 185.2 175.4 173.2 The best predicted height is enter your response here cm. (Round to two decimal places as needed.) Would the result be helpful? A. No, because the description would be the same regardless of shoe print length. B. Yes, because the description would be based on an actual shoe print length. C. Yes, because the correlation is strong, so the predicted…