44386

d) Hence test whether ? is significant. Give reasons for your answer.

Please analyze these tables one by one . Explain as table 1 and table 2.

Please help me with question d, e, f, g, h, and I. Thank you.

Drug use The 2011 World Drug Report investigated theprevalence of drug use as a percentage of the populationaged 15 to 64. Data from 22 European countries are shown in the following scatterplot and regression analy-sis. (Source: World Drug Report, 2011. www.unodc.org/ unodc/en/data-and-analysis/WDR-2011.html) Dependent variable is CocaineR-squared = 38.1%s = 0.724 with 22 - 2 = 20 degrees of freedomVariable Coefficient SE(Coeff) t-Ratio P-ValueIntercept 0.35707 0.2757 1.295 0.21Cannabis% 0.14264 0.0406 3.512 0.002a) Explain in context what the regression says.b) State the hypothesis about the slope (both numericallyand in words) that describes how use of marijuana isassociated with other drugs. c) Assuming that the assumptions for inference are satis-fied, perform the hypothesis test and state your conclu-sion in context. d) Explain what R-squared means in context.e) Do these results indicate that marijuana use leads tothe use of harder drugs? Explain.

Q1 Data displayed in this graph were standardized. True or false? Q2 Based on this graph, one can accurately estimate shoe size heritability to be 0.8676. True or false?

What is the degree of the correlation between sales and display area in square feet? The sales of 14 store branches and display area(in square feet) were obtained. The objective is to predict sales in terms of area of dispslay. Data were encoded into MS Excel. Output is shown below. REGRESSION STATISTICS Multiple R 0.954 R Square 0.910 Adjusted R square 0.902 Standard Error 936.85 Observations 14 Coefficients Standard t stat Error Intercept 901.25 513.02 1.76 Size 1.69 0.15 11.00 CHOICES A. 0.15, low positive B. 0.910, high positive C. 0.954, high positive D. 0.902, high positive

A) Which point from the data has the largest residual? B) Explain what the residual means in context. Is this point an outlier? An influential point? The residual means that when the swim time is______, the observed heart rate is about  _____  beats less than the predicted rate. When this point is removed, it has an effect on the regression line, so it is influential. The point is not an outlier, because the residual is less than twice the standard deviation.

mean of x = 2.882, standard deviation = 1.634  Mean of y = 2.588, standard deviation = 0.246  The correlation coefficient is 0.159 slope coefficient for regression line = .0239 y intercept = 2.52 write the regression model

Report the correlations between the three independent variables (age, educ and Protestant) and your dependent variable (childs). Which category had the correlation that was the weakest?

/was/ui/v2/assessment-player/index.html?launchid=831489a9-d255-4984-8d47-074c80bc17d6#/question Problems Question 2 of 8 Two variables are defined, a regression equation is given, and one data point is given. Weight Training = Weight = = maximum weight capable of bench pressing (pounds) number of hours spent lifting weights a week The data point is an individual who trains 5 hours a week and can bench 150 pounds. 99 + 11.7(Training) (a) Find the predicted value for the data point and compute the residual. Enter the exact answers. Residual = i II Predicted value = eTextbook and Media 3' " lbs lbs C D 6 O W

• 1. Open Excel Data Sheet • 2. Select the Data Tab • 3. Select Dată Analysis • 4. Select Regression • 5. Key in Data Explain each step in conducting an Excel multiple regression analysis

O Equation: EQX02 Workfile: TEMP:Untitled\ View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable INTEREST Method Least Squares Date: 09/10/20 Time: 21:33 Sample (adjusted) 2010M03 2019M12 Included observations: 118 after adjustments Variable Coeficient Std Error 1-Statstic Prob. 0.3778 0.0000 INTEREST(-1) INTEREST(-2) UNEMP(-1) UNEMP(-2) -0.149421 1.366098 0.365452 0.006215 0017402 0.168770 0 087917 0.088887 0.074166 0.075188 -0.885355 15.53853 4111411 0.083802 0.0001 09334 0.8174 0.231441 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statstic Prob(F-statistic) 0.992907 Mean dependent var 0.992655 SD. dependent var 0.102165 Akaike info critenon 1.179453 Schwarz criterion 104.2976 Hannan Quinn criter. 3954.322 Durbin-Watson stat 0.000000 2.776102 1.192120 -1.683011 1.565609 -1.635342 1.877536 Consider the above ARDL model for INTEREST (interest) where UNEMP is the unemployment rate. What is the degrees of freemdom of…

estion 3 of 38 university and gathers their freshman year GPA data and the high school SAI score reported on each of their college applications. He produces a scatterplot with SAT scores on the horizontal axis and GPA on the vertical axis. The data has a linear correlation coefficient of 0.506701. Additional sample statistics are summarized in the table below. Variable Sample Sample standard Variable description mean deviation high school SAT score x 1504.291401 Sx = 105.782904 %3D y freshman year GPA y = 3.240805 Sy = 0.441205 r = 0.506701 slope 0.002113 Determine the y-intercept, a, of the least-squares regression line for this data. Give your answer precise to at least four decimal places. tems of use Thelp about us குசங் careers 2:30 PM 10/24/20 o耳 国 @ hp

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?

▼ Set background Clear frame 6.2 2) The program used to create this scatterplot found the line-of-best-fit and reported the r-squared value as r^2 = 0.805 for the relationship between arm-span and height for several individuals. What is the correlation coefficient? Is it positive or negative? Explain how you know. 1850- 1800- 1750- 1700- 00 1650- 1600- 1550- arm-span (cm) height (cm) 160.0 R Sq Linear-0805 : =S Open c 2 IN

Having the variation data regression line r=0.931 and the coefficient of determination is 0.867.. And the variation of 91.6% is explained by the regression line.. About the unexplained​ variation? [ ]% of the variation is unexplained and is due to other factors or to sampling error. ​(Round to one decimal place as​ needed.)

The equation that represents the average least squared error and the regression line on the scatterplot is called a:     regression equation     multiple regression line     partial correlation equation     slope and intercept line

Choose the answer

Having the variation data regression line r=0.931 and the calculated coefficient of determination of 0.867.. And explained variation of the data of 86.7%.. About the unexplained​ variation? [ ] % of the variation is unexplained and is due to other factors or to sampling error. ​(Round to one decimal place as​ needed.)

What percentage of the variation in  can be explained by the corresponding variations in  and  taken together?

Where is the slope term and intercept on this table (attached)?

A study is conducted involving 17 infants to investigate the association between gestational age at birth, measured in weeks, and birth weight, measured in grams. By the used of the table what is the coefficient relationship between the gestational age at birth and birth weight of the infants? Please make a Decision and Conclusion, refer to the image below for interpretation.

Find correlation coefficient between the exchange and expenditure from the datagiven below:   Obtain the regression equation of exchange on expenditure expenses and find out theexpected exchange of a firm when expenditure is Rs. 25 lakhs. Also find coefficientof determination and interpret your result.

Exam 1 Final Exam Mean 79.48 73.15 SD 10.60 11.68   The correlation between the two exams is r = 0.602 Determine the regression equation for this data, then predict the final exam grade of a student who got a 76 on the first test.

Why this type of plot is used in analysing regression models

Analysis of Variance Source DF SS MS Regression 1 Residual Error 13 0.2364 Total 14 11.3240 What is the value for MSR (Mean Square for Regression)?

Pls. help me in my stat about CORRELATION ANALYSIS, SIMPLE REGRESSION ANALYSIS AND PATH ANALYSIS IN R