An agricultural experimenter divided atract of land into seven plots of equalsize. Each plot was treated withdifferent levels of fertilizer to determinewhether the level of fertilizerapplication affects yield. The results areshown below:PlotA5.062Level of iertikrer,3.04.04.5ESS60Ted5357565859What is the equation of the regressionline?OY= 45.4288 - 2.8571XOY = 45.4288 + 2.8571XOY=45.4288X + 2.8571OY = 45.4288X - 2.8571O none of the above

3.0 53 159 9 3.5 57 199.5 12.25 4.0 56 224 16 4.5 54 243 20.25 5.0 62 310 25 5.5 59 324.5…

Answered: An agricultural experimenter divided a…

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

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

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.…
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sg ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract: The regression equation is Price = B + ÞBedroom + yHouse Size + ALot Size Predictor Coef SE Coef T P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 s= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression Residual 3 76501718347 25500572782 **** Error 96 60109046053 626135896 Total 99 1. Fill in the missing values *, **, and **** 2. Use the p-value approach to determine if o is significant at the 5% significance level
An agent for a real estate company in a large city would like to be able to predict the monthly rental cost for apartments, based on the size of the apartment, as defined by square footage. A sample of eight apartments in a neighborhood was selected, and the information gathered revealed the data shown below. For these data, the regression coefficients are b, = 89.7175 and b, = 1.0703. Complete parts (a) through (d). Monthly Rent (S) Size (Square Feet) 900 1,450 850 1,500 2,000 900 1,825 1,300 o 850 1,350 950 1,200 1,900 700 1.350 1.050 ..... a. Determine the coefficient of determination, r, and interpret its meaning. 2= 0.843 (Round to three decimal places as needed.) What is the meaning of ? O A. r measures the proportion of variation in apartment size that can be explained by the variation in monthly rent. O B. r measures the proportion of variation in apartment size that cannot be explained by the variation in monthly rent. O C. measures the proportion of variation in monthly rent…
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.
Suppose a commercial developer in Vereeniging consider to purchase a group of small office buildings in an established business district. He uses multiple linear regression analysis, which was based on a sample of 35 office buildings, to estimate the value of an office building in a given area based on the following variables. Y = Assessed value of the office building (in Rand) X1= Floor space in square meters X2= Number of offices X3= Age of the office building in years Answer the questions that follow by typing only the letter of the correct option (A, B, C, D or E) in the answer spaces provided. Variablesy: Valuex1: Floor Spacex2: Officesx3: Age Model Fitting StatisticsR^2 = 0.9752Adj R^2: ? Regression Coefficients Beta Parameter Standard b Parameter Standard Estimates Error of Beta Estimates Error of b t Statistic Prob > |t|Intcpt…
A data set consists of these points: (2, 4), (4, 7), (5, 12). Malinda found the regression equation to be ŷ = 2.5x- 1.5. Is she correct? A. No. Both a and bare incorrect. O B. No. The value for b is incorrect. C. No. The value for a is incorrect. O D. Yes. This is the correct equation.
Please use linear regression test statistics, and defined everything -- all parts.

SEE MORE QUESTIONS

Recommended textbooks for you

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

College Algebra

Algebra

ISBN:

9781337282291

Author:

Ron Larson

Publisher:

Cengage Learning

Trigonometry (MindTap Course List)

Trigonometry

ISBN:

9781337278461

Author:

Ron Larson

Publisher:

Cengage Learning

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

College Algebra

Algebra

ISBN:

9781337282291

Author:

Ron Larson

Publisher:

Cengage Learning

Trigonometry (MindTap Course List)

Trigonometry

ISBN:

9781337278461

Author:

Ron Larson

Publisher:

Cengage Learning

Algebra & Trigonometry with Analytic Geometry

Algebra

ISBN:

9781133382119

Author:

Swokowski

Publisher:

Cengage

College Algebra

Algebra

ISBN:

9781938168383

Author:

Jay Abramson

Publisher:

OpenStax

Functions and Change: A Modeling Approach to Coll…

Algebra

ISBN:

9781337111348

Author:

Bruce Crauder, Benny Evans, Alan Noell

Publisher:

Cengage Learning

SEE MORE TEXTBOOKS