Compute Karl Pearson's coefficient of correlation between per capitaNational Income and per capita Consumer Expenditure from the data given below :Per CapitaConsumer Expenditure000)Per CapitaNational Income"000)Years1998249237199925123820002482362001252240200225824520032692552004271254200527225220062802582007275251Also calculate probable error.Solution. Since the actual means of X and Y variable are not whole number, we shouldapply the assumed mean method of finding correlation

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Answered: Compute Karl Pearson's coefficient of…

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 researcher speculates that because of differences in diet, Japanese children have a lower mean blood cholesterol level than U.S. children do. Suppose that the mean level for U.S. children is known to be 175. Let ? represent the true mean blood cholesterol level for Japanese children. What hypotheses should the researcher test? H0: ? = 175 versus Ha: ? > 165H0: ? = 175 versus Ha: ? < 185 H0: ? = 175 versus Ha: ? < 175H0: ? = 175 versus Ha: ? > 175H0: ? = 185 versus Ha: ? > 175
15) Fine the sum of products (SP) and sum of squares (SS) for the variables of interest mentioned in the study above. Then find the correlation between the two variables of interest. (Round all answers to 2 decimal points) a) SP = b) SSbullying = c) SSprejudice = d) r =
Consider 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 1459.95122 1 80 190.65061 None of the above 81 206.320988 Coef. Std. Err. 8.439024 3.049595 -5.219512 2.156389 MS t Number of obs F(1, 80) Prob > F R-squared O The Nets lost more games than they won in 2014 P>|t| 2.77 0.007 -2.42 0.018 Adj R-squared = Root…
A researcher is studying the intensity of hurricanes that entered the Gulf of Mexico between 1975-2015 and the average water temperature of the Gulf of Mexico at the hurricane's peak strength. What is the independent and dependent variable in this study?
An investigator has determined that the correlation between measures of anxiety and depression is -0.65. What kind of relationship is this? Positive Negative Invalid data Nonlinear
2.)Use the following data where Y is the dependent and X is the independent variable: SALES EXPERIENCE Y ('000TL) X(Years) 114 61 129 135 117 6 17 11 7 12 Test the hypothesis that there is a significant correlation between Y and X at 1% level of significance.
Consider 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]…

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