The data table below contains the amounts that a sample of nine customers spent for lunch (in dollars) at a fast-food restaurant. Complete parts (a) through (f).Click here to view page 1 of the table of critical values of t.Click here to view page 2 of the table of critical values of t.**Data:**4.17, 4.93, 5.98, 6.49, 7.41, 7.46, 8.34, 8.59, 9.76---**a.** At the 0.01 level of significance, is there evidence that the mean amount spent for lunch is different from $6.50?State the null and alternative hypotheses.- $ H_0: \mu = 6.50 $- $ H_1: \mu \neq 6.50 $(Type integers or decimals. Do not include the $ symbol in your answer.)Identify the critical value(s).The critical value(s) is(are) 3.3554, -3.3554.(Round to four decimal places as needed. Use a comma to separate answers as needed.)Determine the test statistic.The test statistic is __. (Round to four decimal places as needed.)

Answered: The data table below contains the…

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 data in the accompanying table are from a paper. Suppose that each person in a random sample of 49 male students and in a random sample of 88 female students at a particular college was classified according to gender and whether they usually or rarely eat three meals a day. Find the test statistic and P-value. (Use SALT. Round your test statistic to three decimal places and your P-value to four decimal places.) Usually Eat3 Meals a Day Rarely Eat3 Meals a Day Male 26 23 Female 35 53
A random sample of 11 professional athletes produced the following data, where x is the number of endorsements the player has and y is the amount of money the player made (in millions of dollars). (Comma separated lists of the data are also provided below the table to ease in copying the data to R.) Number of Endorsements (x) Amount Player Made in Millions of Dollars (y) 5 0.1 8. 20.6 8. 20.1 14 7 15.6 4 5.8 21 3 4.9 4 12.5 8. 18.5 8 21.5 x: 5, 8, 8, 7, 7, 4, 5, 3, 4, 8, 8 y: 0.1, 20.6, 20.1, 14, 15.6, 5.8, 21, 4.9, 12.5, 18.5, 21.5 1. Find the best fit line for the data. y =
Let x represent the hemoglobin count (HC) in grams per 100 milliliters of whole blood. The distribution for HC is approximately normal with μ = 14 for healthy adult women. Suppose that a female patient has taken 12 laboratory blood samples in the last year. The HC data sent to her doctor is listed below. We would like to know if the data indicates this patient has significantly high HC compared to the population. 14,19,16,14,19,19,14,21,17,17,14,17 Give the p-value and interpret the results. a) p = 0.0012; Based on 5% significance level, I will reject the null hypothesis and conclude this patient has a high HC level. b) p = 0.0012; Based on 5% significance level, I will fail to reject the null hypothesis and conclude this patient does not have a high HC level. c) p = 0.0023; Based on 5% significance level, I will reject the null hypothesis and conclude this patient has a high HC level. d) p = .1053; Based on 5% significance level, I will fail to reject the null hypothesis and…
Researchers wondered whether the size of a person's brain was related to the individual's mental capacity. They selected a sample of 5 females and 5 males and measured their MRI image pixel counts and IQ scores. Females Males MRI IQ MRI IG The data is reported to the right. Complete parts (a) through (d) below 139 858,472 140 955,003 935,494 924,059 1.079.550 1,001.121 Click the icon to view the critical values table. 991,305 138 141 857,782 833,868 790,619 133 135 132 141 135 140 AMRI 1,080,000- AIO 145 AIO 145- AMRI 1,080,000 780,000 130 130 780,000 130 780,000 780,000 130 1,080,000 145 1,080,000 MRI 145 MRI (b) Compute the linear correlation coefficient between MRI count and IQ. Are MRI count and IQ linearly related? Select the correct choice below and, if necessary, fill in the answer box to complete your choice. (Round to three decimal places as needed.) A. Yes, MRI count and IQ are linearly related since the linear correlation coefficient is O B. No. MRI count and IQ are not…
The data found below measure the amounts of greenhouse gas emissions from three types of vehicles. The measurements are in tons per year, expressed as CO2 equivalents. Use a 0.025 significance level to test the claim that the different types of vehicle have the same mean amount of greenhouse gas emissions. Based on the results, does the type of vehicle appear to affect the amount of greenhouse gas emissions? : Click the icon to view the data. What are the hypotheses for this test? Data Table O A. Ho: H1 = H2 =H3 H: At least one of the means is different from the others. Туре с O B. Ho: H1 # H2 * H3 Туре А 6.2 Type B 8.2 7.7 Hyi Hy = H2 =H3 5.8 7.3 7.6 6.2 8.4 8.8 OC. Ho: H1 = H2 = H3 H: H1 # H2 #H3 5.7 7.8 8.8 6.9 8.8 9.3 6.1 7.7 8.1 O D. Ho: At least one of the means is different from the others. 7.9 5.7 7.3 5.9 7.3 7.8 H: H1 =H2 = H3 5.6 8.1 5.6 Determine the test statistic. F = (Round to two decimal places as needed.) Print Done Identify the P-value. Click to select your answer(s).…
Let x represent the hemoglobin count (HC) in grams per 100 milliliters of whole blood. The distribution for HC is approximately normal with μ = 14 for healthy adult women. Suppose that a female patient has taken 12 laboratory blood samples in the last year. The HC data sent to her doctor is listed below. We would like to know if the data indicates this patient has significantly high HC compared to the population. 22,17,20,17,17,14,16,21,15,21,15,22 Give the p-value and interpret the results. a) p = .1053; Based on 5% significance level, I will fail to reject the null hypothesis and conclude this patient does not have a high HC level. b) p = .0562; Based on 5% significance level, I will fail to reject the null hypothesis and conclude this patient does not have a high HC level. c) p = 0.0003; Based on 5% significance level, I will fail to reject the null hypothesis and conclude this patient does not have a high HC level. d) p = 0.0003; Based on 5% significance level, I will reject the…
The vapor pressure of 1-chlorotetradecane at several temperatures are tabulated below. T (ºC) P∗ mm Hg 98.5 1 131.8 5 148.2 10 166.2 20 199.8 60 215.5 100 What error is there in using two-point linear interpolation to find the value of vapor pressure at 185ºC?
A researcher collected how many grams of fat people on a specific diet consumed at breakfast and at lunch. The data for a sample of 8 people is shown in the table below. xx 11.3 8.2 7.2 3.6 2.3 2.5 2.7 0.4 yy 13.7 10.7 10.2 7.2 6.3 6.5 6.1 4.1 xx = grams of fat in breakfastyy = grams of fat in lunchThis data can be modeled by the equation ˆy=0.84x+4.07.y^=0.84x+4.07.Given this, how many grams of fat in lunch would be expected for a person who consumed 1.2 grams of fat at breakfast? Round to 1 decimal place.Answer =
The data table below contains the amounts that a sample of nine customers spent for lunch (in dollars) at a fast-food restaurant. Complete parts (a) through (d). Click here to view page 1 of the table of critical values of t. Click here to view page 2 of the table of critical values of t. 4.17 4.93 5.98 6.49 7.41 7.46 8.34 8.59 9.76 C a. At the 0.01 level of significance, is there evidence that the mean amount spent for lunch is different from $6.50? State the null and alternative hypotheses. Ho: H = 6.50 H: μ # 6.50 (Type integers or decimals. Do not include the $ symbol in your answer.) Identify the critical value(s). The critical value(s) is (are). (Round to four decimal places as needed. Use a comma to separate answers as needed.)
Calculate the correct t-statistics based on the information below. X1 = 200 X2 = 198 n1 = 17 n2 = 17 s1 = 2.45 s2 = 2.35 Let us assume that two groups of students at Tarleton are being compared on their average weights. Do you think the groups are different in terms of weight (measured in pounds)?
Use the t3 I calculator.
1:15 (a) Which variable is the explanatory variable? OA. One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in a certain region. Complete parts (a) through (h) below. Click the icon to view the housing data. Square Footage Selling Price (b) Draw a scatter diagram of the data. Choose the correct scatter diagram below. Ay 4500- 000 1000 mylab.pearson.com/ + ® : 3 4500 Data Table Q Square Footage, x 2148 3231 1177 1988 3064 2735 4146 2215 2625 1629 1773 3887 Print ||| OB. r= 0.899 (Round to three decimal places as needed.) = AX 4500- 1000+++ 150 750 Q (c) Determine the linear correlation coefficient between square footage and asking price. Done Ay 750- Vo) 1 LTE2 150- O 1000 Selling Price ($000s), y D 371.1 382.2 197.6 339.9 614.9 364.7 632.7 377.7 427.5 285.9 268.9 701.4 4500 .... .... Q X D. Ay 750- 41% 150+ 1000 4500

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