Use RStudio to fit a simple linear regression model to the data below. Please submit acopy of your code and any appropriate output (a photo/screenshot will be sufficient).300? Is the fitted linear regression modelWhat is the 95% prediction interval for xo =appropriate for this data, and which assumption appears to be violated if not?dataset <- data.frame (с (294, 247, 267, 358, 423, 311, 450, 534, 438, 688, 630, 709, 627,1021, 615, 700, 999, 1250, 1015, 850, 980, 1650, 1025, 1200, 1500),у 3 с (30, 32, 37, 44, 47, 49, 56, 62, 68, 80, 84, 88, 97, 97,100, 106, 109, 112, 117, 128, 130, 135, 160, 180, 210)X =%3D

Let x be the independent variable and y be the dependent variable. The simple linear regression…

Answered: Use RStudio to fit a simple linear…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Please answer it using any spreadsheet. Or you can answer it manually but please do show your full solution. Thanks!!!
A linear regression equation has a slope of 4 and an intercept of 2. What is the predicted value of Y for an X of 8? Edit View Insert Format Tools Table
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help asap please. I will upvote.
The accompanying data are the caloric contents and the sugar contents (in grams) of 11 high-fiber breakfast cereals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. Calories, x Sugar, y 140 6 200 10 160 6 160 9 170 10 180 16 190 13 210 18 190 19 170 10 170 10 The equation of the regression line is ŷ = ______ x + ______ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (a) x = 150 cal, (b) x = 90 cal, (c) x = 175 cal, (d) x = 208 cal…
Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child ( height), height of the mother ( mothersheight ), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 2 104.004228 8.49446952 37 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE = = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What are the null and alternative hypotheses…
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…
I need help with finding test statistic, thanks
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The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 769 828 993 1126 937 824 D Temperature (°F) 68.8 67.5 81.9 87.1 78,3 75.6 What is the regression equation? =ロ·ロ× (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) Help me solve this View an example Get more help - Clear all Check answer 4:51 PM 66°F 全x D 4/15/2022 Sunny
Q5/ Use Linear Regression to fit the following data: X 1 2 4 5 6 Y 4 10 10 9 3
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 784 838 822 949 1188 813 Temperature (°F) 65.7 67.8 66.2 79.9 92.3 73.5 What is the regression equation? What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000chirps per minute are? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an…

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