The following hypotheses are to be testedHo : p = 0H1 : p + 0at a0.05 level of significance.%3|Given: The value of the test statistic is t = 6.035.Complete the following:• We reject the null hypothesis when t <• We conclude thatO the between variation is smaller than the within variation.or when t >O the between variation is greater than the within variation.O the intercept is zero.there is not a linear association between X and Y.the intercept is not zero.O there is a linear association between X and Y. The relationship between body mass index (BMI) and systolic blood pressure in males 50 years of age is investigated. A random sample of n = 13 malesis selected and their BMI and systolic blood pressures are measured.Let X be the body mass index (BMI) and Y the systolic blood pressure of males, 50 years of age.Given:The average and variance of the BMI is X = 26 and Var(X) = 15.026.The average and variance of the systolic blood pressure is Y = 126 and Var(Y) = 423.The covariance between X and Y is Cov(X,Y) = 69.87.For the estimated regression equation Y = Bo + B, X, it was found that B1 = 4.65.

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Answered: Ho : p = 0 Hị : p+ 0 at a = 0.05 level…

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 physical therapist wanted to know whether the mean step pulse of men was less than the mean step pulse of women. She randomly selected 54 men and 70 women to participate in the study. Each subject was required to step up and down a 6-inch platform. The pulse of each subject was then recorded. The following results were obtained. Two sample T for Men vs Women N Mean StDev SE Mean Men Women 98% CI for mu Men - mu Women (- 12.20, - 1.00) T-Test mu Men = mu Women (vs H2 O C. Ho: H1 = H2; Ha: H1 #H2 (b) Identify the P-value and state the researcher's conclusion if the level of significance was a = 0.01. What is the P-value? P-value =
Answer the questions using the data below. Use α = 0.05. moto cor 3 JOHO7OO 1 1 0 0 a) Compute the correlation. b) Obtain/compute the appropriate values for H₁: p < 0. Critical Value = ; Test Statistic = Decision: -Select--- c) Compute the corresponding effect size(s) and indicate magnitude(s). If not appropriate, input and/or select "na" below. Effect Size = ; Magnitude: ---Select--- d) Make an interpretation based on the results. There was a significant positive relationship between y and x. There was a significant negative relationship between y and x. There was no significant relationship between y and x. Submit Answer
The following sample contains values of the price and quantity sold of a particular commodity. Use quantity sold as the dependent variable Y. Price (X) 6.00 3.00 7.00 1.00 2.00 8.00 Quantity sold (Y) 53 67 48 76 70 28 ∑x}=27, ∑y=342, ∑x2=163, ∑xy=1295, ∑y2 = 21062, n=6. d. Find the coefficient of determination and interpret .
The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of a = 0.01. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. O A. OB. Best Actor (years) 70- 20- 20 70 Best Actress (years) Best Actor (years) The linear correlation coefficient is r= (Round to three decimal places as needed.) xample Get more help. 70- ||||||||| THHHH 20+ 20 Best Actr 11111 H ||||||||| Qu 70 Q *** Best Actor (years) C. 20+ 20 P +||||| HHHH 70 Best Actresses and Best Actors 29 Best Actress 29 30 29 59 32 32 43 Best Actor 45 37 40 43 49 50 59 48 O D. Best Actor (years) 64 37 70- 20+ 20 D M 23 42 53 55 43…
Consider the following data on price ($) and the overall score for six stereo headphones tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). Brand Price ($) Score A 180 76 В 150 69 C 95 63 70 54 E 70 38 F 35 24 (a) The estimated regression equation for this data is ŷ 21.258 + 0.327x, where x = price ($) and y = overall score. Does the t test indicate a significant relationship between price and the overall score? Use a = 0.05. State the null and alternative hypotheses. Ho: B1 + 0 Ha: B1 Ho: B1 Ha: B1 + 0 = 0 O Ho: Po = 0 Ha: Bo + 0 O Ho: B1 2 0 Ha: B1 < 0 O Ho: Po + 0 Hai B = 0 Find the value of the test statistic. (Round your answer to three decimal places.) Find the p-value. (Round your answer to four decimal places.) p-value
a. Report and interpret the P-value for Fisher's exact test with (i) Ha: 0 > 1 and (ii) Hạ: 0 # 1. Explain how the P-values are calculated. b. Find and interpret the mid P-value for Ha: 0 > 1. Summarize advantages and disadvantages of this type of P-value. Table 3.14 Data for Exercise 3.18 on Therapy for Cancer of Larynx Cancer Controlled Cancer Not Controlled Surgery Radiation therapy 21 15 23
O REGRESSION AND CORRELATION Linear relationship and the sample correlation coefficient Shas Below are four bivariate data sets and the scatter plot for each. (Note that each scatter plot is displayed on the same scale.) Each data set is made up of sample values drawn from a population. y 11 10- 94 S- 1.0 6.7 1.0 7.4 10- 2.0 9.4 2.0 9.1 3.0 4.0 3.0 7.0 4.0 9.1 6+ 4.0 5.3 5- 5.0 4.7 5.0 8.0 4. 3 2- 7.0 6.4 6.0 1.7 6.0 5.1 7.0 | 4.6 8.0 10.1 9.0 5.1 8.0 6.5 9.0 5.7 10.0 3.7 10.0 8.0 | Figure 1 Figure 2 t 1.0 3.2 1.0 1.0 2.0 2.0 2.0 4.2 3.0 3.3 3.0 3.0 4.0 4.9 4.0 4.0 5.0 4.5 5.0 5.0 6.0 6.8 6.0 6.0 7.0 5.8 7.0 7.0 8.0 7.3 8.0 8.0 9.0 6.6 9.0 9.0 10.0 8.2 Figure 3 10.0 10.0 Figure 4 Explanation Check e 2021 McGraw-H Education. All Rights Reserved. Terms of Use I Privacy Accessibilty P Type here to search
The graph to the right portrays the decision criterion for a hypothesis test for a population mean u. The null hypothesis for the test is Ho: H= Ho- The curve in the graph is the Do not reject Ho I Reject Ho normal curve for the test statistic under the assumption that the null hypothesis is true. Complete parts (a) through (f) below. Reject I Ho I 3D 0.01 0.01 -2.054 2.054 a. Determine the rejection region. O.A. zs -2.054 O B. -2.054 szs2.054 O C. zs - 2.054 or z22.054 O D. z>2.054 b. Determine the nonrejection regon. O A. z> - 2.054 B. -2.054
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AutoSave Off Ch13 60v13_10e (1) - File Home Insert Draw Page Layout Formulas Data Review View à From Text/CSV là Recent Sources T Queries & Connections là From Web LA Existing Connections Properties Get Refresh Data A From Table/Range All - A Edit Links Get & Transform Data Queries & Connections v X v fx H19 C D F ANOVA table 2 Source SS df MS 3 Regression 4 Residual 5 Total 1870.5782 1 1870.5782 41.39 1265.4934 28 45.1962 3136.0716 29 6. 7 8 Regression output 9 Variables 10 Intercept Coefficients Std. Error t(df=28) 13.76015 3.106 2.914 11 Distance-X 3.77085 7.977 6.427 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Identify if the statement is TRUE or FALSE 1. The correlation coefficient measures the strength of association between the population. 2. The pearson product moment correlation coefficient is used to measure linear association. 3. The population correlation coefficient (p) is an estimate of sample correlation coefficient (r). 4.The closer r is to 0, the stronger linearity between variables. 5. In hypothesis testing for the correlation, rejecting null hypothesis means there is no significant correlation between the variables in the population.
Use the given data set to complete parts (a) through (c) below. (Use α= 0.05.) 13 12.75 X y OA. a. Construct a scatterplot. Choose the correct graph below. Ay 16- 10 7.45 12- 8- 4- 8 6.77 Click here to view a table of critical values for the correlation coefficient. 0- 0 4 8 12 16 Q G OB. Ay 16- 12+ 8 4- 0 9 7.11 Bi 4 8 12 16 11 7.81 Q C 14 8.84 O C. Ау 16- 12- 8- 6 6.07 4- 0- 0 4 8 12 16 Q Q ✔ 4 5.38 12 8.14 D. Ay 16- 12- 8- 4- 0- 0 7 6.41 ******** · 4 8 12 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r= (Round to three decimal places as needed.) Q 5 5.72 Q

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