Concept explainers
A marketing research firm suggests to a comp any that two possible competing products can genera te incomes X and Y (in millions) that are
However, the company would prefer the one with the smaller variance if, in fact,
Which product does the company select?
Want to see the full answer?
Check out a sample textbook solutionChapter 5 Solutions
Pearson eText for Probability and Statistical Inference -- Instant Access (Pearson+)
- A bakery is considering buying one of two gas ovens. The bakery requires that the temperature remain constant during a baking operation. A study was conducted to measure the variance in temperature of the ovens during the baking process. The variance in temperature before the thermostat restarted the flame for the Monarch oven was 3.5 for 15 measurements. The variance for the Kraft oven was 4.6 for 24 measurements. Does this information provide sufficient reason to conclude that there is a difference in the variances for the two ovens? Assume measurements are normally distributed and use a 0.02 level of significance. (a) Find F. (Give your answer correct to two decimal places.)(ii) Find the p-value. (Give your answer correct to four decimal places.)(b) State the appropriate conclusion. Reject the null hypothesis, there is significant evidence to show a difference in variances.Reject the null hypothesis, there is not significant evidence to show a difference in variances. Fail to…arrow_forwardQ1. An engineering statistics class has 265 students; 60% are electrical engineering majors, 10% are industrial engineering majors, and 30% are mechanical engineering majors. A sample of four students is selected randomly without replacement for a project team. Let X and Y denote the number of industrial engineering and mechanical engineering majors, respectively (Hint: range for both variables is 0..4). Determine the following: (a) fXY (x, y) (b) fX (x ) (c) E (X ) (d) fY|3 (y) (e) E (Y|X = 3) (f) V (Y|X = 3) (g) Are X and Y independent? Why?arrow_forwardConsider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin; - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team==== "Brooklyn Nets" Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1 80 Coef. Std. Err. MS 81 206.320988 8.439024 3.049595 -5.219512 2.156389 1459.95122 190.65061 t Number of obs F (1, 80) Prob > F R-squared. Adj R-squared = Root MSE P>|t| 2.77 0.007 -2.42 0.018 82 7.66 0.0070 0.0874 0.0760 13.808 [95% Conf. Interval]…arrow_forward
- The demand for a commodity is given by Q = Bo + B₁P+u, where Q denotes quantity, P denotes price, and u denotes factors other than price that determine demand. Supply for the commodity is given by Q You, where v denotes factors other than price that determine supply. Suppose that u and v both have a mean of zero, have variances o and o2, and are mutually uncorrelated. Solve the two simultaneous equations to show how Q and P depend on u and v.arrow_forwardA 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…arrow_forward4. Find if A and B are independent, positively associated or negatively associaied from the data given below : (A) = 470, , (B) = 620 , (ĂB) = 320, N= 1000 beoubenarrow_forward
- A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 72 individual that have been using their program for 18 months. For each individual person, the company records the individual's weight when they started the program 18 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (183, 157) would be for a specific person and it would indicate that the individual started the program weighing 183 pounds and currently weighs 157 pounds. In other words, they lost 26 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.831. 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…arrow_forwardA study claims that girls and boys do not do equally well on math tests taken from the 2nd to 11th grades (Chicago Tribune, July 25, 2008). Suppose in a representative sample, 344 of 430 girls and 369 of 450 boys score at proficient or advanced levels on a standardized math test. (You may find it useful to reference the appropriate table: z table or t table)Let p1 represent the population proportion of girls and p2 the population proportion of boys.a. Construct the 95% confidence interval for the difference between the population proportions of girls and boys who score at proficient or advanced levels. (Negative values should be indicated by a minus sign. Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal places.) b. Select the appropriate null and alternative hypotheses to test whether the proportion of girls who score at proficient or advanced levels differs from the proportion of boys.multiple choice 1 H0: p1 − p2 = 0; HA: p1 − p2 ≠ 0…arrow_forwardSuppose you just bought one share of stock A and want to hedge it by shorting stock B. How many shares of B should you short to minimize the variance of the hedged position? Assume that the variance of stock A's return is o?; the variance of B's return is o?; their correlation coefficient is p. Please show your derivation by attaching a file below. Hint: 1. we don't restrict the solution to be an integer, it can be a non-negative value 2. we don't set constraints for the target returnarrow_forward
- A world wide fast food chain decided to carry out an experiment to assess the influence of income on number of visits to their restaurants or vice versa. A sample of households was asked about the number of times they visit a fast food restaurant (X) during last month as well as their monthly income (Y). The data presented in the following table are the sums and sum of squares. (use 2 digits after decimal point) ∑ Y = 393 ∑ Y2 = 21027 ∑ ( Y-Ybar )2 = SSY = 1720.88 ∑ X = 324 ∑ X2 = 14272 ∑ ( X-Xbar )2 = SSX = 1150 nx=8 ny=11 ∑ [ ( X-Xbar )( Y-Ybar) ] =SSXY=1090.5 PART A Sample mean income is Answer Sample standard deviation of income is Answer 90% confidence interval for the population mean income (hint: assume that income distributed normally with mean μ and variance σ2) is [Answer±Answer*Answer] 90% confidence interval for the population variance of income (hint: assume that income distributed normally with mean μ and variance σ2) is…arrow_forward13.arrow_forwardYou are interesting in the relationship between the amount of fertilizer used to treat avocado trees and the output of the trees. You gather the following information: Total trees = 100 Total fertilizer used 50 gallons %3D Total avocados produced 10,000 %3D Covariance (Avocados per tree, Fertilizer per tree) = 40 %3D Variance(Avocados per tree) = 4 A.) The average value of your independent variable is B.) The average value of you dependent variable is C.) The estimated value of the slope coefficient, b1, is D.) The estimated value of the intercept, b0, is E.) Assuming that an avocado tree had 1 gallon of fertilizer used on it, we would expect avocados produced in a given season.arrow_forward
- Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage LearningBig Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt