If the relationship between fish length in cm (x)and fish weight in gr (t) is expressed in theY = B₁ + B₁ × + ε. Based on the existing data,we want to do an F test for the hypothesisHo :B₁₂ = 0 and H₂ :B₁₂+0 at a significancelevel of a = 5%a Determine the F test statistic by completingthe following ANAVA tableSource of vanationdbregressionmisguidedTotal??11ЈК??82.200b) Determine the test rejection are aI Give a test conclusion.RK66-333?F?Paper Star Y 242X29023,2 24,0340 36323,9 26,343026,5450 50026,8 26,839045027,6 27,650028,547550028,4 28,7

The independent variable is fish length The dependent variable is fish weight We have to test the…

Answered: If the relationship between fish length…

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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Based on the sample data set: (0,0) ( 2,3) (3,3) (6,4) (9,8) A. Construct the 90% confidence interval for the slope B1 of the population regression line B. find the Coefficient of determination using the formula r2=B1SSxy / SSyy.
In an experiment to determine the relationship between force on a wire and resulting extension, the following data was obtained: Force (N) 10 20 30 40 50 60 70 Extension (mm) 0.22 0.40 0.61 0.85 1.20 1.45 1.7 Determine the most appropriate type of regression line for this data, explaining how you arrive at you answer. Determine of the coefficient of correlation for this data. Comment on the considered accuracy values using this method.
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ONA model is developed for forecasting of sale and the effects of three independent variables , advertising expenditure (X1), Price (X2), and time (X3) resulted in the following. Regression Statistics Standard Error 232.29 Table 1: ANOVA df SS MS F Regression 3 53184931.86 ? ? Residual ? 1133108.30 ? Total 24 54318040.16 Table 2: regression Coefficients Standard Error t Stat Intercept 927.23 1229.86 ? Advertising (X1) 1.02 3.09 ? Price (X2) 15.61 5.62 ? Time (X3) 170.53 28.18 ? Fill in the blanks in table 1 and table 2 . What is the total number of observations . Write down the…
9:33 AA www-awn.aleks.com O REGRESSION AND CORRELATION Predictions from the least-. Managers of an outdoor coffee stand in Coast City are examining the relationship between (hot) coffee sales and daily temperature, hoping to be able to predict a day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by y, in dollars) and the maximum temperature (denoted by x, in degrees Fahrenheit) for each of fifteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1. Temperature, x (in degrees Coffee sales, y (in dollars) Fahrenheit) 68.3 1787.6 38.9 2311.0 72.9 1684.0 2200 58.8 1979.5 63.4 1816.4 2000 75.8 1997.6 46.9 2131.7 71.0 1973.9 100 38.7 2018.2 1400 53.9 1597.5 45.9 1996.1 75.4 1501.0 50.9 2266.3 81.7 1574.5 Figure 1 45.5 1798.9 Send data to Excel After deciding on the appropriateness of a linear model relating coffee sales and maximum temperature, the managers…
A multiple regression was estimated using the SEK method and the results are given below. Based on these estimates alone, multiple Explain the level of linearity, varying variance and cascading dependency problems. Bi: 4,1234 B2: -0,2189 B3: -1,7862 sh:3,1223 R?: 0,9820 R*: 0,9750 F: 10,89 F tablo:3,07 sh:4,4420 sh:0,3179 D.W.: 0,2558 d1:0,385 dy:1,685
You want to determine if diet impacts body weight. You recruit 60 subjects, assigning 20 each to either one of two dietary interventions or to maintain their normal diet. You measure body weight before and after the intervention and calculate the change in body weight (post minus pre weights). To determine the diet effect on the calculated change in body weight, you would use a .Assume all assumptions are met for a parametric test. Factorial ANOVA One-way repeated measures ANOVA O Factorial repeated measures ANOVA One-way ANOVA
A student used multiple regression analysis to study how family spending (y) is influenced by income (x) family size (x2), and addition to savings(x3). The variables y, x1, and x3. The variables y, x1, and x3 are measured in thousands of dollars . The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficient Standard Error Intercept 0.0136 X1 0.7992 0.074 X2 0.2280 0.190 X3 -0.5796 0.920 Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? Carry out a test to determine whether y is significantly related to the independent variables. Use a 5% level of significant. Carry out a test to see if X3 and y are significantly related. Use a 5% level of significance
Shown below is a portion of a computer output for regression analysis relating y (dependent variable) and x (independent variable). ANOVA df SS Regression 1 24.061 Residual 10 67.979 Coefficients Standard Error Intercept 11.064 2.049 x −0.566 0.301 (a) What has been the sample size for the above regression analysis? (b) Perform a t-test and determine whether or not x and y are related. Let ? = 0.05. State the null and alternative hypotheses. (Enter != for ≠ as needed.) H0: Ha: 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 = What is your conclusion? .
6
i)Test individually whether the slope coefficients are significant at 10% significance level. ii)Test the overall significance of the estimated regression at 1% significance level.
The value obtained for the test statistic, z, in a one-mean z-test is given. Also given is whether the test is two tailed, left tailed, or right tailed. Also is given the P-value.A left-tailed test: z = -1.17 P-value: 0.1210 Use technology to create a scatter plot of the data from the previous question. Include the regression line. (Hand drawn graphs will not be accepted.) The explanatory (input) variable and the response (output) variable must be clearly labeled, within the context of this problem.

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