If the condition for using the empirical rule is met, why should that rule be used instead of Chebyshev’s rule?
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Q: 1) What is the slope(b1) and what is its statistical interpretation?
A:
If the condition for using the
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- 1) The population regression function for the 2-variable model is Y,= B, + B,X, +U, Where Ui is used as a surrogate for all the variables omitted from the regression but collectively effect Y₁, why then not use a multiple regression with all the necessary variables included?You are a researcher who wants to know what the mean (µ) level of anxiety would be for the whole population if they were all receiving a new anti-anxiety therapy. You can’t give the therapy to the whole population, so you give it to a sample, and you get M = 32.1 as the average anxiety level for the sample on the therapy. What is the reason that you can’t just simply assume that µ = 32.1? You didn’t use random assignment Sampling error Descriptive statistics Inferential statisticsX X zy Section 5.4- QNT/275T: Statistics x + 598163/chapter/5/section/4 for Decision Making home > nce between two population means 4.1: Hypothesis test for the difference between two population means. Jump to level 1 A clinical researcher performs a clinical trial on 14 patients to determine whether a drug treatment has an effect on serum glucose. The sample mean glucose of the patients before and after the treatment are summarized in the following table. The sample standard deviation of the differences was 8. Before treatment What is the test statistic? Ex: 0.123 Check What type of hypothesis test should be performed? Select Select Left-tailed z-test Paired t-test Two-tailed z-test Unpaired t-test Next After treatment 75 Sample mean glucose (mg/dL) What is the number of degrees of freedom? Ex: 25 Does sufficient evidence exist to support the claim that the drug treatment has an effect on serum glucose at the a = 0.05 significance level? Select 81 MESA 81101 2 hp 3 I
- Please send me the question in 30 minutes it's very urgent plzA weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 10, you determine that r = 0.80. a) What is the value of the t test statistic t STAT ? b) At the a = 0.05 level of significance, what are the critical values? c) Based on your answers to (a) and (b), what statistical decision should you make?
- ANSWER THE FOLLOWING QUESTION.1. If you accidentally forget to use the robust standard errors option in your regression software, then: A) both your coefficients and standard errors will be different than in case with robust SE B) only your standard errors will be different than in case with robust SE C) only your coefficients will be different than in case with robust SE D) only the R squared will be different than in the case with robust SE 2. We saw that the OLS estimator from a regression of test scores on a dummy for class size (X=1 for STR<20) was positive and equal to 7.4. If average family income is negatively correlated with average class size in California school districts, we can expect the OLS estimator to be: A) larger than the true population value of the difference in means B) smaller than the true population value of the difference in means C) equal to the correlation between test scores and class size D) equal to the true population value of the difference in meansFor a sample of 74 monthly observations the regression of the percentage return on gold (y) against the percentage change in the consumer price index (x) was estimated. The sample regression line, obtained through least squares, was as follows: y = -0.003 + 1.11x The estimated standard deviation of the slope of the population regression line was 2.31. Test the null hypothesis that the slope of the population regression line is 0 against the alternative that the slope is positive.
- I have a doubt when it comes to this reasoning : Imagine I have a variable that is correlated to Y and to X1 in a linear regression model. If I ommit it it will result in Omitted Variable Bias but if I include it, would it result in perfect multicolinearity and therefore for example a solution is to include control variables ? Is this right ? Thanks.Students who complete their exams early certainly can intimidate the other students, but do the early finishers perform significantly differently than the other students? A random sample of 37 students was chosen before the most recent exam in Prof. J class, and for each student, both the score on the exam and the time it took the student to complete the exam were recorded. a. Find the least-squares regression equation relating time to complete (explanatory variable, denoted by x, in minutes) and exam score (response variable, denoted by y) by considering Sx = 15, sy = 17,r = 39.706, x = 90, ỹ = 78 b. The standard error of the slope of this least-squares regression line was approximately (Sp) is 20.13. Test for a significant positive linear relationship between the two variables exam score and exam completion time for students in Prof. J's class by doing a hypothesis test regarding the population slope B1. Write the null and Alternate hypothesis and conclude the results. (Assume that…You wish to test whether a particular drug manages to bring body temperature down. So, you conduct a pilot study where 47 people receive the drug, and 45 people receive a placebo. The body temperatures of patients from the treatment group are group 1 (variable X1); those from the placebo group are group 2 (variable X2). What is the research hypothesis? mu1 > mu2 mu1 ≠ mu2 mu1 < mu2 mu1 = mu2