Lot Size Regression Problem Nov 20 SOLVED

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: учах+b a-1.25 b-35.644 r2 .541696 r=-0.736 Use this to predict the number of situps a person who watches 10 hours of TV can do (to one decimal place)

Please do only the last two parts

Find the regression​ equation, letting overhead width be the predictor​ (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.1cm. Can the prediction be​ correct? What is wrong with predicting the weight in this​ case? Use a significance level of 0.05. The regression equation is y^=_____+_____x.   overhead width (cm) 8.2 7.4 9.6 7.9 7.6 8.7 weight (kg) 159 156 241 144 154 207   n α=0.05 α = 0.01 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19 0.456 0.575 20 0.444 0.561 25 0.396 0.505 30 0.361 0.463 35 0.335 0.430 40 0.312 0.402 45 0.294 0.378 50 0.279 0.361 60 0.254 0.330 70 0.236 0.305 80 0.220 0.286 90 0.207 0.269 100 0.196 0.256 n α = 0.05 α = 0.01

persor Develop an estimated multiple regression equation that relates risk of a stroke to the person's age, systolic blood pressure, and whethet Let xi represent the person's age. Let x2 represent the person's systolic blood pressure. Let represent whether the person is a smoker. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sgn even d there is a sign before the blank. (Example -300)

Why this type of plot is used in analysing regression models

please help me answer for my data analysis class

The data show The chest size and weight of several bears find regression equation, letting chest size be the independent variable then find the best predicted weight of a bear with a chest size of 51 inches is the result close to the actual weight of 422 pounds use a significance level of 0.05 Chest size : 45, 50, 43, 43, 52, 52. Weight : 352, 374, 275, 314, 440, 367.

Write a report on your findings. Predictor Constant X_MoneySupply Y_lagIncome S = 2328 Coef 12,718 0.4405 0.7805 R-Sq= 99.4 % Use the report to estimate the model. SE Coef 5392 0.3393 0.1616 T 2.36 1.30 4.83 R-Sq(adj) = 99.4 % P 0.031 0.213 0.000 Y₁ = + x₁ +t-1 Yt (Round the constant to the nearest integer as needed. Round the coefficients to four decimal places as needed.)

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Correlation and linear regression

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Please refer to attached image, tq

Please no written by hand solution Identify the residual plot that shows the linear regression model is a good fit for the data.

Adjusted value of R2.  =       Interpretation of the adjusted value of R2

**Based on the regression results, answer the following questions** Data are collected on the income (measured in $1000’s of $’s), house value (measured in $1000’s of $’s), years in a home, age, sex (=1 for male, =0 for female), and the amount outstanding on a mortgage (measured in $1000’s of $’s). The dependent variable is income. Based on the regression results, answer the following questions b) What is the estimated regression equation? c) How much of the variation in income is explained by the regressors? d) What is the standard error of the error term in the regression equation?

**Based on the regression results, answer the following questions** Data are collected on the income (measured in $1000’s of $’s), house value (measured in $1000’s of $’s), years in a home, age, sex (=1 for male, =0 for female), and the amount outstanding on a mortgage (measured in $1000’s of $’s). The dependent variable is income. Based on the regression results, answer the following questions e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the predicted value of income for a person that has been in a house for 5 years, is 38 years old, is a male, has a house valued at $250,000, and has $100,000 left on their mortgage? (g) What is the effect on the income of a person being a male versus a female?