An agricultural experimenter divided a tract of land into seven plots of equal size. Each plot was treated with different levels of fertilizer to determine whether the level of fertilizer application affects yield. The results are shown below: 5O What is the equation of the regression line? OY= 45.4288 - 2.8571X OY= 45.4288 + 2.8571X OY=45.4288X + 2.8571 OY- 45.4288X - 2.8571 O none of the above

An agricultural experimenter divided a tract of land into seven plots of equal size. Each plot was treated with different levels of fertilizer to determine whether the level of fertilizer application affects yield. The results are shown below: 5O What is the equation of the regression line? OY= 45.4288 - 2.8571X OY= 45.4288 + 2.8571X OY=45.4288X + 2.8571 OY- 45.4288X - 2.8571 O none of the above

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.4: Linear Regression

Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

See similar textbooks

Similar questions

The sheet called HousePr contains data on prices of houses that have sold recently and two attributes of the house – the number of bedrooms and the size. Column 1 is the selling price of the house in thousands of dollars and column 2 is the size in hundreds of square feet.a. Draw a scattergram of price vs size. Discuss whether this scattergram supports an assumption of a linear relationship between price and size.b. Using Excel, obtain the equation of the linear regression line that fits this data for price vs. size.c. Using relevant Excel output, discuss whether the true slope of the regression line is different from zero.d. What is the expected price for a house with size 2000 square feet? Using relevant Excel output, discuss whether the margin of error of this expected price will be low or high.e. Using Excel, obtain the equation of the linear regression line that fits this data for price vs. number of bedrooms. Is the true slope different from zero?f. What is the expected price for…
The file Galton on D2L contains the 928 observations Francis Galton used in 1885 to estimate the relationship between the heights of parents and the heights of their children. The column Children refers to the height (in inches) of a child, and the column Mid-Parents refers to the average height (in inches) of the mother and father of that child. You can download this file into Excel and Minitab. a. Calculate the regression Height of Children = a +b (Height of Mid-Parents). b. Calculate the average for Height of Children, and calculate the average Height of Mid-Parents. c. Create a new variable in Minitab which is the Height of Children measured in terms of deviations from its mean. Call this new variable y. Also, create a new variable in Minitab with is the Height of Mid-Parents measured in terms of deviations from its mean. Call this new variable x. Calculate the regression y = a + bx. You can create the new y and x variables in Excel of Minitab, whichever you find more convenient.…
A vending machine company operates coffee vending machines in office buildings. The company wants to study the relationship between the number of cups of coffee sold per day and the number of persons working in each building. Data were collected were collected by the company and presented below. Number of Number of Cups of f. Make a copy of the scatter diagram in this item. Draw the line that best fits in the scatter diagram using the regression equation. persons Coffee Sold working at Location g. Locate the (X,). Describe its location in relation to the other plotted data. 15 20 10 15 h. Give a practical interpretation of the values of a and b. 16 20 i. Show that the regression equation can be expressed in the form: (y - y) = b(x - x) 18 25 22 30
Find the regression line of the points: (12.7, 18.7), (9.1, 17.2), (15.3, 14.5), (19.5, 12.9)
The 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…
The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks are entered into the Microsoft Excel Online file below. Use the XLMiner Analysis ToolPak to perform your regression analysis in the designated areas of the spreadsheet. Open spreadsheet a. Develop an estimated regression equation with the amount of television advertising as the independent variable (to 2 decimals). Revenue = TVAdv b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables (to 2 decimals). Revenue = TVAdy + NewsAdv c. Is the estimated regression equation coefficient for television advertising expenditures the same in part (a) and in part (b)? d. Predict weekly gross revenue for a week when $4.6 thousand is spent on television advertising and $3.7 thousand is spent on newspaper advertising (to 2 decimals)? in thousands
Refer to the data set:Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 5.
Please use linear regression test statistics, and defined everything -- all parts.
Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from a data set, the resulting regression equation is Weight=-274 +0.426 Length + 12.1 Chest Size. The P-value is 0.000 and the adjusted R² value is 0.925. If an additional predictor variable of neck size (in.) is included, the P-value becomes 0.000 and the adjusted R² becomes 0.933. Why is it better to use values of adjusted R² instead of simply using values of R²? Choose the correct answer below. C O A. The unadjusted R² can only be calculated for regression equations with two or fewer predictor variables, while the adjusted R² can be calculated for regression equations with any number of predictor variables. O B. The unadjusted R² increases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. OC. The unadjusted R² can only be calculated for regression equations with P-values greater than 0, while the adjusted R² can be calculated for…
Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from a data set, the resulting regression equation is Weight= -274 +0.426 Length + 12.1 Chest Size. The P-value is 0.000 and the adjusted R² value is 0.925. If an additional predictor variable of neck size (in.) is included, the P-value becomes 0.000 and the adjusted R² becomes 0.933. Why is it better to use values of adjusted R² instead of simply using values of R²? Choose the correct answer below. C O A. The unadjusted R² can only be calculated for regression equations with P-values greater than 0, while the adjusted R² can be calculated for regression equations with any manner of P-value. O B. The unadjusted R² increases or remains the same as more variables included, but the adjusted R² is adjusted for the number of variables and sample size. OC. The unadjusted R² decreases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. O D. The…
The regression equation for for the association between BMI and total cholesterol level is: y = 28.07 + 6.49x A.) Suppose a participant has a BMI of 26. What would we estimate the total cholesterol to be? B.) Suppose two individuals have a mean BMI that differs by 3 units. What is the estimated difference in total cholesterol. C.) What ranges of BMI should the equation be used to predict total cholesterol?
Lillian conducted a small survey of her friends and family. She asked them how many hours per week they spend reading digital documents (newspapers, blogs, books, etc.), and their age. She created the scatter plot below with the results she obtained. Draw the regression line that best represents this scatter plot and determine its equation.