According to "Reproductive Biology of the Aquatic Salamander Amphiuma tridactylum in Louisiana,"t the size of a female salamander's snout is correlated with the number of eggs in her clutch. The following data are consistent with summary quantities reported in the article. Partial Minitab output isalso included.Snout-Vent LengthClutch Size324553215531605317054190572005727058175582455921563170632406424567280The regression equation isY = -133 + 5.92xPredictorCoefStdevTPConstant-133.0264.302.070.06085.9191.1275.250.00023 = 33.90R-sq = 69.7R-sq (adj) = 67.2%Additional summary statistics are given below.n - 14= 56.5= 201.4Ex? = 45,597 Ey? = 613,550 Exy = 164,690You can use the Distribution Calculators page in SALT to find critical values and/or p-values to answer parts of this question.(a) What is the equation of the regression line for predicting clutch size based on snout-vent length? (Let x = snout vent length and y = clutch size. Round your intercept to two decimal places and your slope to three decimal places.)ý = -133.0165 + 5.9194x(b) What is the value of the estimated standard deviation of b? (Round your answer to three decimal places.)192.5495

Use the Excel and Perform the Regression. Followings are the Steps to perform the Regression 1) Open…

Answered: You can use the Distribution…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Why the regression line is a straight line rather than a curved line?
I’m taking a statistics and probability class. Please get this correct because I want to learn. I have gotten wrong answers on here before
A researcher is interested to measure returns to schooling. He ran the regression below: w = a + b*School where w is the hourly wage, 'School' measures years of schooling and b is the coefficient on schooling. Fill in the missing blanks to make the statement correct. Omitting an important variable а. biases b only if it is not related to the 'School' variable. b. does not affect the estimate of b. It only affects the standard error of the estimated coefficient. C. biases b and affects the standard error of the estimated coefficient. d. biases b only if it is related to the 'School' variable.
I was wondering specifically about part D and how to interpret my findings.
There are 6 parts for this Question. Please help
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 3000chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1004 952 1237 1116 1177 1249 Temperature (°F) 83.1 76 95.1 87.5 92.1 88.4 What is the regression equation? (^ over y)=_____+_____x (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000chirps per minute? The best-predicted temperature when a bug is chirping at 3000 chirps per minute is ____°F. (Round to one decimal place as needed.) What is wrong with this predicted value? Choose the correct answer below. A. It is…
You 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?
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 63 inches. Is the result close to the actual weight of 562 pounds? Use a significance level of 0.05. Chest_size_(inches) Weight_ (pounds)58 41450 31265 49959 45059 45648 260 What is the regression equation?^y = ____ + _____ x (round to one decimal place as needed.)What Is the best predicted weight of a bear with a chest size of 63 inches? ^y =____ pounds (round one decimal as needed)Is the result close to the actual weight of 452 pounds?(a) This result is very close to the actual weight of the bear.(b) This result is close to the actual weight of the bear.(c) This result is exactly…
Explain the process of Computing the Regression Line?
Is it reasonable to interpret the y-intercept of the regression line? Why or why not? One home that is 1,750 square feet is listed at $590,000. Is this home's price above or below average for a home of this size? Use residuals and show your work to answer. footaget) ## (Intercept) 21.14411 136.31449 0.155 0.87954 ## footage 0.28388 0.08516 3.333 0.00667 ** ## Residual standard error: 71.64 on 11 degrees of freedom ## Multiple R-squared: 0.5025, Adjusted R-squared: 0.4573 ## F-statistic: 11.11 on 1 and 11 DF, p-value: 0.006671
Describe regression variation in terms of variation in Y.
Using the data in the Excel spreadsheet "auto.xlsx", estimate a regression to answer the following question. How much does a 1 inch increase in LENGTH corresponds to a _________________ dollars increase in PRICE. Use negative values if it results in a decreased price. Round your answers to two decimals.

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