Formulate research problems andhypotheses to test the effect between 2variables (variable X and variable Y). Thefollowing presents quantitative data fromthe measurement results of variables Xand Y from a number of individuals(sample) taken randomly from a certainpopulation. The distribution of themeasurement data is as follows:No. Resp. 1 2 345 6 789 10 11 12 13 14 15 16Var.X11 22 9 5 25 10 13 12 17 16 20 15 18 19 23 28Var.Y17 30 12 9 34 15 20 19 24 22 29 21 25 27 31 36Based on these data, solve the followingstatistical problems:b. Draw the regression line!

b) The regression analysis is conducted here by using EXCEL. The software procedure is given below:…

Answered: Formulate research problems and…

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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The better-selling candies are often high in calories. Assume that the following data show the calorie content from samples of M&M's, Kit Kat, and Milky Way II. M&M's Kit Kat Milky Way II 240 235 200 210 205 208 220 245 202 250 215 190 240 230 180 Test for significant differences among the calorie content of these three candies. State the null and alternative hypotheses. Ho: Median MM = MedianK = Median,ww H: Median MM + Median KK + MedianmW O Ho: MedianMM = MedianKK = Median Mw H: Median MM > MedianK > MedianMw O Ho: Not all populations of calories are identical. H: All populations of calories are identical. O Ho: All populations of calories are identical. H: Not all populations of calories are identical. O Ho: MedianMM * Mediankk * Median Mw H: Median MM = MedianKk = Median,Mw Find the value of the test statistic. (Round your answer to two decimal places.) 8.62 Find the p-value. (Round your answer to three decimal places.) p-value =.004769
Let uss. HMS: HLS, Hsuv and HMV represent the mean costs per mile for small sedans, medium sedans, large sedans, SUV 4WDS, and minivans respectively. What are the hypotheses for this test? O A. Ho: Hss HMs = HLS = HSUV = HMv H: Not all the means are equal. O B. Ho: Hss= HMs HLS HSUV = Hmv H2: Hss HMS HLs Hsuv HMV O C. Ho: Hss HMS HLS HSUV HMV H: Hss = HMS = PLs = Hsuv = PMv O D. Ho: Not all the means are equal. H Hss = HMS PLs=Hsuv = PMv
Suppose that x and y are two variables of a population with x a predictor variable and y a response variable. a. The distribution of all possible values of the response variable y corresponding to a particular value of the predictor variable x is called a _______ distribution of the response variable. b. State the four assumptions for regression inferences.
Formulate research problems and hypotheses to test the effect between 2 variables (variable X and variable Y). The following presents quantitative data from the measurement results of variables X and Y from a number of individuals (sample) taken randomly from a certain population. The distribution of the measurement data is as follows: No. Resp. 1 2 3 4 56 789 10 11 12 13 14 15 16 Var.X 11 22 9 5 25 10 13 12 17 16 20 15 18 19 23 28 Var.Y 17 30 12 9 34 15 20 19 24 22 29 21 25 27 31 36 Based on these data, solve the following statistical problems: c. How big is Y if X is 50? Do the interpretation!
(Use SPSS) A random sample of nine male race horses at a Fauquier County stable yielded the following data on age of horse (months) and time to run a mile (seconds). Age of Horse (x) 22 27 62 47 38 ☐32 55 50 58 Time to Run a Mile (y) 96 102 158 125 113 107 142 139 141 a. Construct a scatterplot of the data. What does it suggest about the relationship between the age and speed of male race horses in Fauquier County? b. Assuming that the simple linear regression model is appropriate, obtain the equation of the estimated regression line. c. What percentage of the observed variation in Time to Run a Mile can be explained by the resulting model? d. Check the regression assumptions using a normal probability plot of the residuals and a plot of the explanatory variable values versus the studentized residuals. e. A race horse trainer in Fauquier County claimed that there is a useful linear relationship between the two variables. Do you agree? Carry out a formal hypothesis test to support your…
A bivariate table is one in which a. a dependent variable is cross-classified by two or more independent variables b. a single variable is broken down into two categories c. there are two rows and two columns d. a dependent variable is cross-classified by an independent variable
Two brands of batteries are tested, and their voltage is compared. The data follow. Test the claim that voltage of brand X is less than voltage of brand Y. Assume that both variables are normally distributed. use a 0.05 level of significance. Brand X Brand Y sample mean = 8.2 Sample mean= 8.4 O, = 0.3 n, = 27 oy = 0.1 ny = 30
1. 2. 4. 1. 2. The distribution of a sample of 100 test scores is mound-shaped and symmetrical, with a mean of 50 and a variance of 144. 3. a) b) c) 4. d) 3. a) a) A sample of 200 people were given a test. The distribution of the test scores was mound- shaped and symmetrical with a mean of 100. One person, whose test score was 125, was found to be at the 84th percentile. b) d) Answers: b) Approximately how many scores are equal to or greater than 74? What score corresponds to the 75th percentile? If the lowest and highest scores in this sample are 14 and 89, respectively, what is the range of the scores in standard deviation units? b) Assume that the 100 test scores still have a mean of 50 and a variance of 144, but now have a strongly negatively skewed distribution. At least how many of the scores fall between 32 and 68 in this distribution? What is the Z-score of a person whose test score is 70? Approximately how many people obtained scores greater than 135? Approximately how many…
A statistical program is recommended. Consider the following data for a dependent variable y and two independent variables, x, and x,. X1 X2 12 94 47 10 108 25 17 112 51 16 178 40 94 51 19 175 7 170 36 12 117 59 13 142 76 16 211 The estimated regression equation for the data is ý = -18.4 + 2.01x, + 4.74x2. (a) Develop a 95% confidence interval for the mean value of y when x, = 51 and x, = 16. (Round your answers to three decimal places.) to (b) Develop a 95% prediction interval for y when x, = 51 and x, = 16. (Round your answers to three decimal places.) to 30 74
1. Birds can regrow feathers if they are lost. A researcher was interested in whether newly regrown feathers in the tails of northern flickers differed in colour (yellowness in particular) compared to older feathers. To test this, they measured the yellowness of one new and one randomly selected old feather on each of 20 birds. A plot of their data and the results of their analysis are shown below. Yellowness 160 150 140 130 new X Feather old Welch Two Sample t-test = data: Yellowness by Feather t = 1.5832, df 37.986, p-value 165 sample estimates: mean in group new mean in group old 147.9623 143.3000 160 New 155 150 145 140 135 = 0.1217 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -1.299296 10.623962 T T T T T 130 135 140 145 150 155 160 Old a) From the results above, what is the null hypothesis and what statistical conclusion do you make concerning it?
The accompanying data were read from a plot (and are a subset of the complete data set) given in an article. The data represent the mean response times for a group of individuals with closed-head injury (CHI) and a matched control group without head injury on 10 different tasks. Each observation was based on a different study, and used different subjects, so it is reasonable to assume that the observations are independent. Study 1 y= 2 3 4 5 6 7 8 9 10 Mean Response Time CHI Control 250 360 475 525 610 740 880 920 1010 1200 304 492 432 659 683 922 1044 1421 1329 1481 1815 (a) Fit a linear regression model that would allow you to predict the mean response time for those suffering a closed-head injury from the mean response time on the same task for individuals with no head injury. (Round your answers to four decimal places.) (b) Do the sample data support the hypothesis that there is a useful linear relationship between the mean response time for individuals with no head injury and the…
An experiment was designed to study oil additives that could reduce polluting the air. Two additives were considered in the study. The two additives X1 and X2 were controlled and the level of the pollution Y is observed. The data were as follows: Y X1 X2 3.9 1.5 2.2 7.5 1.5 4.5 4.4 1.7 2.2 8.7 1.8 4.4 9.6 5.5 4.3 8.5 5.5 4.5 Find the regression equation Is the model valid? Which independent variable is linearly related to Y?

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