9. Regression of y= Bo + B1X11 + B2X12 + B3 X13 + BaX14 + û¡ yieldsthe following results in tabular form. The tabulated t- statistics is 2.4 , 1.96and 1.64 for onefive and ten percent significance levels respectively.State the null and alternative hypotheses for each & Identify those variablesaffecting the dependent variable.Independent variablesCoefficientsStd. Err.Xi11731.784255.4491Xi2667.8642250.4062Xi3-38.44927200.0217Xi4-48.14751423.5669Bo3559.713243.1407

There are 4 independent samples and 1 dependent variable. The partial regression analysis output is…

Answered: 9. Regression of y=Bo + B1xi1 + 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 is given as follow. xi 2 6 9 13 20 Vi 7 18 9 26 23 The estimated regression equation for these data is y7.6 + .9x. Compute SSE, SST, and SSR (to 1 decimal) SSE SST SSR What percentage of the total sum of squares can be accounted for by the estimated regression equation (to 1 decimal)? What is the value of the sample correlation coefficient (to 3 decimals)?
Conduct a hypothesis for whether consumption and income are linearly related using ? =0.01. The standard error of the slope is 0.144. Slope = 0.75, Intercept = 0, sample:Income 9, 11, 5, 8, 2, 9, 12Consumption 7, 7, 2, 7, 2, 8, 9 Step 1: State the null and alternative hypotheses.Step 2: Choose the significance level.Step 3: Calculate the test statistic.Step 4: Find the critical value(s).Step 5: Compare the test statistic to the critical value(s).Step 6: State the conclusion.
Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.1 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (a) Compute the coefficient of determination, R?. R? % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in is explained by the least-squares gression model. (Round to one decimal place as needed.)
Need help writing a null hypothesis for the bivariate relationship shown in the SPSS output.
Here are the scatter plots for two sets of bivariate data with the same response variable. The first compares the variables x & y. The second compares the variables w & y 00⁰0 889 Which explanatory variable has a stronger relationship with the response variable y? The first variable (x) has a stronger relationship with the response variable y. The second variable (w) has a stronger relationship with the response variable y.
In the above regression of air quality on other variables in question 2, R-squared is 0.3829. How do you interpret it?
o pis pe Suppose a doctor measures the height, x, and head circumference, y. of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y = 0.185x+ 12.276. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 (a) Compute the coefficient of determination, R?. R2 = % (Round to one decimal place as needed) (b) Interpret the coefficient of determination k Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. Enter your answer in each of the answer boxes. Save for Later DUE RTTT:DY PIVT Score: o:5SYO Tor Tv attempts 3:35 PA- a 2/22/202 Type here to search insert prt sc 4+ backsp %23 6. 8.
In a multiple regression, which of the following tests can be used to determine if the relationship between the dependent variable and the set of independent variables is significant? The Coefficient Of Determination R-Squared for each coefficient of the X variables & an F- Statistic Test for the overall regression F-Statistic tests for each coefficient & a t-test for the overall regression The Coefficient Of Determination R-Squared and/or an F-Statistic Test for the overall regression & t-tests for each coefficient of the X variables t-tests for each coefficient and for the overall regression
c) Show that the coefficient of determination, R², can also be obtained as the squared correlation between actual Y values and the Y values estimated from the regression model where Y is the dependent variable. Note that the coefficient of correlation between Y and X is Eyixi r = And also that ỹ = ŷ (18.75)
The local utility company surveys 12 randomly selected customers. For each survey participant, the company collects the following: annual electric bill (in dollars) and home size (in square feet). Output from a regression analysis appears below: Bill 13.45 + 4.39*Size Coefficients Estimate Std. Error (Intercept) 13.45 Size 4.39 0.54 0.2 We are 90% confident that the mean annual electric bill increases by between dollars and dollars for every additional square foot in home size. Round your answers to three decimal places and enter in increasing order.
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be
There is a dataset of size n = 51 and is for the 50 states and the District of Columbia in the United States. The dependent variable is year 2002 birth rate per 1000 females 18 to 19 years old and independent variable is the violent crime rate (per 1000 population). A simple linear regression model is run with the results given below. What is the Pearson correlation coefficient between x and y variables? The R squared of the model? What kind of relationship there is?

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