What would be a good questions to use the hypothesis test for the slope (b1) ? Hypothesis Test for the Slope (b₁)To test the null hypothesis Hō: ß₁ = 0 versus H₁: B₁ # 0Know thisfor conuptquestiont =b₁√MSE/√S XXSlidewhere to/2 is a value of the t-distribution with n - 2 df. 35

As the student has requested only a good question to use the hypothesis test for the slope of…

Answered: What would be a good questions to use…

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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A researcher wants to make an equation that will predict a person's support for domestic surveillance from a variety of demographic characteristics (e.g., age, income). What method will they use? A) Multiple regression B) Correlation C) Two-factor ANOVA D) One-sample t-test
The table below gives the age and bone density for 5 women. Use the equation of the regression line, y= b0 + b1x, for predicting a women's bone density based on her age. The correlation coefficient may or may not be statically significant for the data given. Remember it wouldn't be appropiate to use regression line to make a prediction if the correlation coefficient isn;t statically significant. (y has a "hat" on the top) age 39 51 54 56 67 bone density 355 349 347 315 313 Find the estimated slope. Rund your answer to three decimal places. Find the estimated y-intercept. Round your answer to three decimal places. Determine the value of the dependent variable y at x+ 0 (y has a "hat" onthe top) Find the estimated value of y when x = 51. Round your answer to three decimal places. Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the valueof the…
< Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 40 61 62 68 69 Bone Density 357 350 343 340 315 Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places. Table Copy Data Next
A professor decides to investigate the relationship between midterm exam score and final exam score (in points ) of students in her introductory statistics class after taking a sample of students she finds r2=0.74 and the regression equation is final exam score=40+0.95 a correct interpretation of r2 =0.74 would be ? A) 74% of the predicted final exam scores will be correct B) 74 % of the variation in midterm exam score can be explained by the straight line relationship with final exam score c) 74%of students will have higher final exam scores than midterm exam scores D)74% of the variation in final exam score can be explained by the straight line relationship with midterm exam score
A researcher tests whether his students are smarter than the general population. He knows the mean of the population is 100 for the Wechsler Adult Intelligence Scale. He tests the mean of his student’s scores against the mean of the population. What kind of t-test should be used?
Devise two scenarios where a dependent/matched/paired t-test would be appropriate. Be sure to express how you would measure your dependent variable.
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
please use this situation: A small theater company has a linear regression model to estimate y = the concession stand sales in dollars, based on knowing x = the number of people in attendance. The regression equation is: = 6.72x + 11.50 and the correlation coefficient was r = 0.781. The data set saw the number of people in attendance ranging from a minimum of 18 people to a maximum of 170 people. 1) How reliable would it be to make a prediction for the concession sales amount if there were 500 people in attendance? Explain.
A study was conducted in California to investigate the relationship between house size (x in square feet) and house price (y in thousands of dollars). The least-square regression line is given below y= 263.5 + 0.174x R2 = 0.728 a) Interpret the slope of the given regression line b) find the predicted house price for a house size of 120 square feet c) if the actual house price was $449.5 thousand dollars for a house size of 1200 square feet, calculate the residual of the home d) find the correlation coefficient. Round to 3 decimal places
18)The regression equation is intended to be the “best fitting” straight line for a set of data. Whatis the criterion for “best fitting”?
(e) Find the least-squares regression line treating square footage as the explanatory variable.
Draw a scatterplot of the right foot temperature (y) versus the left foot temperature (x). Then draw the least-squares regression line on the graph.

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