Given the following data for age (x) and weight in kg x: 10,14,12,19,11,16 y: 56,67,48,62,65,53 Using Linear regression, estimate the weight of a child with age 15 (Use 4 sf)
Q: Q1) Interpret the following regression line * y = 10.50 – 0.18x
A: The regression analysis is a statistical procedure that allow us to find the linear association…
Q: Consider the following dataset. X Y 1 4 2 2 3 6 4 5 5 1 6 8 7 6 8 10 9 12 10 5 Apply linear…
A: Given data: X Y1 42 23 64 55 16 87 68 109 1210 5
Q: Listed below are the overhead widths (cm) of seals measured from photographs and weights (kg) of…
A: Solution: x y (x-x) (x-x)2 (y-y) (y-y)2 (x-x)(y-y) 7.1 137 -1.35 1.8225 -74.5 5550.25 100.575…
Q: Q: The dataset posted below lists a sample of months and the advertising budget (in hundreds of…
A: Introduction: The response variable is the monthly sales ($1000), and the explanatory variables are…
Q: Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find…
A: It is an important part of statistics . It is widely used .
Q: A study investigated how the content of vitamin A in carrots is affected by the time being cooked.…
A: The least regression equation for the relationship between X and Y is mentioned as; Y = 21.4 –…
Q: The accompanying data are the number of wins and the earned run averages (mean number of earned…
A: Note: Hey there! Thank you for the question. As you have posted a question with multiple sub-parts,…
Q: 1. What percentage of variation in weight is not explained by the regression model? Give your answer…
A: 1) The R2 value is 0.943.
Q: A regression was run to determine if there is a relationship between hours of TV watched per day (x)…
A:
Q: For the population of Jellystone bears, the mean weight is 400 pounds and the mean blood pressure is…
A: Given information x = weight, y = blood pressure
Q: Type the regression equation for “Area” and “Biomass” in context into your document. Interpret…
A: Here we have, The dependent variable: Biomass (y) The independent variable: Area (x)
Q: Find slop of a linear regression model for the following data: x = [1, 2, 3, 4, 5, 6, 7] z = [6.98,…
A: Tablexzx2z2x⋅z17148.77211.34127.922.6314.89218.244.3418163247252325530.8115.2626.336691.7157.8731.54…
Q: A regression analysis was performed to determine if there is a relationship between hours of TV…
A:
Q: The teacher fit a least-squares regression line to data. Given the summary statistics, determine…
A: Given:
Q: The given paired data lists the heights (in inches) of various males who were measured on their…
A:
Q: 12 of R²
A:
Q: Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find…
A: In this case Right Arm (x) is the independent variable and Left Arm (y) is the dependent variable.…
Q: Q5/ Use Linear Regression to fit the following data: 2 3 4 5 6 Y 4 9 10 10 9 8 3
A: We have given that, X :- 0, 1, 2, 3, 4, 5, 6 Y:- 4, 9, 10, 10, 9, 8, 3 Then, We will find the…
Q: A B Math Grade English Grade 86 80 90 88 78 85 88 87 89 90 90 94 91 93 77 80 85 80 78 80
A:
Q: A regression was run to determine if there is a relationship between hours of TV watched per day (x)…
A:
Q: Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from a data set, the resulting…
A: For a new predictor variable, the adjusted R2 is increased from 0.925 to 0.933.
Q: Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Answer How to…
A: It is given that the data in tabulated form.
Q: regress Sleep Age Phone Source df MS Number of obs 1,508 %3D F(2, 1505) 12.27 Model 31.0424157 2…
A: Introduction: Based on the given output, the regression equation is: Sleep = 8.291711 – 0.0543038…
Q: What is the slope? b. Find the correlation coefficient between the age and the life years left.
A: We have given that Left = 60.1- 0.65 is the regression formula (Age) y=60.1-0.65x 96% R-Squared…
Q: elling price and percent of advertising budget spent were into mutiple regression to determine what…
A: The multiple regression model is fitted as: y=β0+β1x1+β2x2+...+βnxn Here, y is the dependent…
Q: Suppose a commercial developer in Vereeniging consider to purchase a group of small office buildings…
A: Given information: The value of coefficient of determination is r2 = 0.9752. The number of predictor…
Q: per ge The proportion of the variability in miles per gallon explained by the relation between…
A: Answer:----. Date:----12/10/2021 r = -0.984 So, r^2 = 0.968256
Q: Determine the regression equation in three different ways (using raw data, deviation data and…
A: Let y = a+bx be the regression equation Y is the dependent variable and x is the independent…
Q: A regression was run to determine if there is a relationship between hours of TV watched per day (x)…
A:
Q: The following data shows the height children with time: Age X, in (months) Height Y, in ( cm) 18 19…
A:
Q: Plot X & Y axis as a scatter plot and describe the plotted data. Calculation (no changes here): Does…
A: Given, data on rainfall and crop yield To make a scatter plot To make regression equations and…
Q: Use the following data to estimate a regression with femur length as the x-variable and tibia length…
A: The variable “Femur Length” is defined as x and the variable “Tibia Length” is defined as y.
Q: Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find…
A: Regression equation y= intercept + slope × X
Q: A sample consists of 500 houses sold in Karachi between January 2020 and December 2020. The multiple…
A: Let Y represents number of house sold. X1=> Age of house X2=> Square footage of the house…
Q: Consider a regression model. The coefficient of determination (R2) gives the proportion of the…
A:
Q: Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find…
A: Step-by-step procedure to find the regression equation using EXCEL: In Excel sheet, enter the data…
Q: The data show the chest size and weight of several bears. Find the regression equation, letting…
A: The independent variable is Chest size. The dependent variable is Weight. The given data represents…
Q: Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find…
A: Introduction: Consider that x is the independent variable and y is the dependent variable. The size…
Q: The regression equation is Price = ß + ØBedroom + yHouse Size + ALot Size Predictor SE Coef Coef T P…
A: According aur policy we can answer only first three subpart for remaining please repost the…
Q: Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find…
A: Use EXCEL to determine the regression equation. EXCEL procedure: Go to EXCEL Go to Data>Data…
Q: Listed below are systolic blood pressure measurements (in mm H) obtained from the same woman. Find…
A: Let y be the systolic blood pressure in the left arm. and x be the systolic blood pressure in the…
Q: 3.) Below is some output from a bivariate regression with respondents' inflation-adjusted personal…
A: In the bivariate regression, the dependent variable(Y) is the inflation-adjusted personal income and…
Q: The accompanying data are the number of wins and the earned run averages (mean number of earned runs…
A: The scatterplot is obtained by using EXCEL. The software procedure is given below: In first column…
Step by step
Solved in 3 steps
- Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $130 million. Use a significance level of α=0.05. A. The regression equation is Y= (Round to one decimal place as needed.) B. The best predicted gross for a movie with a $130 million budget is $ million. (Round to one decimal place as needed.)The data from the table below gives a regression that is a) reliable. b) unreliable. c) unable to determine the reliability.Calculate two lines of regression and calculate a linear regression equation to model the data given below: years (1980,1985,1990,1995,2000) Enrolment ( 21,25,29,39,47)
- Listed below are the overhead widths (cm) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.8 cm, using the regression equation. Can the prediction be correct? If not, what is wrong? Use a significance level of 0.05. Overhead Width (cm) 7.3 7.4 9.8 9.5 8.8 8.5 Weight (kg) 152 187 286 247 237 231 The regression equation is y =+ (x. (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed.)Personal wealth tends to increase with age as older individuals have had more opportunitiesto earn and invest than younger individuals. The following data were obtained from a randomsample of eight individuals and records their total wealth (Y) and their current age (X). See attachment for table with figures State the estimated regression line and interpret the slope coefficient.b. What is the estimated total personal wealth when a person is 50 years old?c. What is the value of the coefficient of determination? Interpret it.d. Test whether there is a significant relationship between wealth and age at the 10%significance level. Perform the test using the following six steps.Step 1. Statement of the hypotheses Step 2. Standardised test statistic Step 3. Level of significance Step 4. Decision RuleYou believe that the price of Zoom Videoconferencing stock and the price of American Airlines stock will move in opposite directions. In order to test this relationship, we do a simple regression with the following variables:A - dependent variable : month end price of American Airlines stockZ - independent variable: month end price of Zoom Videoconferencing stock Data from April 2019 through December 2020 (21 observations) is availableBased on the data, we compute the following:Var (Z) = 20927.702Cov (A,Z) = -899.153E(A) = 20.790E(Z) = 187.530Std Error of Estimate = 6.088TSS = 1476.830 Consider the equation At = b0 + b1 Zt + εtBased on the numbers given above, complete the following table Variable Estimate Std error t-statistic Slope b1 .00941 Constant b0 2.2088 R-square N/A N/A F statistic N/A N/A Are the coefficients (slope and/or constant) significant at the .05 level?
- A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=a+bx b=-0.736 a=32.667 r2=0.576081 r=-0.759 Use this to predict the number of situps a person who watches 6 hours of TV can do.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 sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Сoef SE Coef т 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 3 76501718347 25500572782 Residual Error 96 60109046053 626135896 Total 99 • Is y significantly different from -0.5? Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. Give an interpretation to the term “R-sq" and comment on its value.Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 80 mm Hg. Use a significance level of 0.05. Right Arm 100 99 93 77 77 Q Left Arm 174 168 148 148 146 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is ŷ=+x. (Round to one decimal place as needed.) mm Hg. Given that the systolic blood pressure in the right arm is 80 mm Hg, the best predicted systolic blood pressure in the left arm is (Round to one decimal place as needed.) Data table Critical Values of the Pearson Correlation Coefficient r α = 0.05 α = 0.01 0.950 0.990 0.959 0.878 0.811 0.917 0.754 0.875 0.707 0.834 0.666 0.798 0.632 0.765 0.602 0.735 0.576 0.708 0.553 0.684 0.532 0.661 0.514 0.641 0.497 0.623 0.482…
- The following data shows memory scores collected from adults of different ages. Age (X) Memory Score (Y) 25 10 32 10 39 9 48 9 56 7 Use the data to find the regression equation for predicting memory scores from age. The regression equation is: Ŷ = 4.33X + 0.11 Ŷ = -0.11X + 4.33 Ŷ = -0.11X + 13.26 Ŷ = -0.09X + 5.4 Ŷ = -0.09X + 12.6 Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 28 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 43 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 50 For the calculations, leave two places after the decimal point and do not round:A study investigated how the content of vitamin A in carrots is affected by the time being cooked. In this example: X represents the amount of time, in minutes, that the carrot slices were cooked Y represents the content of vitamin A (in milligrams) in the carrot slices The least-squares regression equation for this relationship is: Y = 23.4 – 0.55X What is the slope of the regression line? Provide a numeric value as shown in the equation.An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.