The following data relate to marks inAdvanced Accounts and Business Statisticsin B.Com. (H.), IIExamination of a particular year inCalifornia University :Mean Marks in Advanced ACcounts =30Mean Marks in Business Statistics =35Standard Deviation of Marks in AdvancedAccounts =10Standard Deviation of Marks in BusinessStatistics =7Coefficient of Correlation between theMarks in Advanced Accounts and BusinessStatistics =0.8Find the two regression lines and calculatethe expected marks in Advanced Accountsif the markssecured by a student in Business Statisticsare 40.

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Answered: The following data relate to marks in…

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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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 Find the intercept for the regression line.
A researcher would like to evaluate the effect of a new reading program for second-grade students. For the past five years, a standardized test given at the end of second grade has produced a mean score of ? = 45. A sample of n = 25 students is placed in the new program and, at the end of the school year they obtain a mean test score of M = 51 with SS = 9600. Based on these data can the researcher conclude that the new program has a significant effect on reading scores. Use a two-tailed test with ? = .05. (a) Using symbols, state the hypotheses for this test.(b) Locate the critical region for ? = .05.(c) Calculate the t statistic for this sample.
What would be the appropriate inferential statistic to evaluate the relationship between: • 'Generation' [Baby Boom (1946-1964), Generation X (1965-1980), Millennials (1981-1996)] • 'Household Income' (in US $) median and interquartile range means comparison (t or ANOVA) correlation coefficient (r) chi-square (x2) mean and standard deviation frequency and percentage
Several bakeries in a town were asked the price for different amounts of donuts at their shop. The scatter plot with Total Cost (in dollars) 876543 ~ TO 0 0 1 Donut Pricing 2 3 4 5 Number of Donuts 6 7 8 line of best fit was created from the data gathered. Part A: Estimate the correlation coefficient. Explain your reasoning for the given value. Part B: How many positive and negative residuals are there? Explain your reasoning. Part C: State the point with the largest absolute value residual and interpret the point in terms of the context of the data.
The following data relate to marks in Advanced Accounts and Business Statistics in B.Com. (H.), Il yr Examination of a particular year in Delhi University : Mean Marks in Advanced Accounts Mean Marks in Business Statistics Standard Deviation of Marks in Advanced Accounts Standard Deviation of Marks in Business Statistics Coefficient of Correlation between the Marks in Advanced Accounts and Business Statistics Find the two regression lines and calculate the expected marks in Advanced Accounts if the marks secured by a student in Business Statistics are 40. = 30 = 35 = 10 = 7 = 0-8
Please answer as many as your allowed too. Thank you :) A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.68b=0.168 (a) Write the equation of the Least Squares Regression line of the formˆyy^= + x(b) Which is a possible value for the correlation coefficient, rr? -1.417 1.417 0.702 -0.702 (c) If a country increases its life expectancy, the happiness index will increase decrease (d) If the life expectancy is increased by 0.5 years in a certain country, how much will the happiness index change? Round to two decimal places.(e) Use the regression line to predict the happiness index of a country with a life expectancy of 69 years. Round to two decimal places.
A researcher found a significant correlation of .12 between gender (coded as 0 = ‘male’ and 1 = ‘female’) and number of friends at university. If the assigned values of gender were changed to 1 = ‘female’ and 2 = ‘male’, how would this affect the correlation? The strength of the relationship would become weaker The amount of variance explained by the relationship would increase It would become nonsignificantThe sign would change to become negative A researcher is trying to predict anxiety (measured on a 7-point scale) from exposure to stress (operationalised as the number of stressful life events participants can recall in the last week). She has found a correlation coefficient of r = .54 between anxiety and stress, with a standard deviation of 4.45 for anxiety and a variance of 17.21 for stress. What other information is needed to calculate b? The sums of squares of stressThe sums of products of anxiety and stress The covariance of anxiety and stressNo other information is…
The maximum weights (in kilograms) for which one repetition of a half squat can be performed and the times (in seconds) to run a 10-meter sprint for 12 international soccer players are shown in the attached data table with a sample correlation coefficient r of - 0.958. A 13th data point was added to the end of the data set for an international soccer player who can perform the half squat with a maximum of 210 kilograms and can sprint 10 meters in 1.99 seconds. Describe how this affects the correlation coefficient r. Use technology. Click the icon to view the data set. Data Table The new correlation coefficient r going from - 0.958 to (Round to three decimal places as needed.) Maximum weight, x Time, y 175 1.81 185 1.79 155 2.06 210 1.42 155 2.07 195 1.62 190 1.69 165 1.88 195 1.59 180 1.64 165 1.97 175 1.91 210 1.99
Researchers at UC San Francisco discovered that highplasma levels of vitamins B, C, D, and E are associated with better cognitive performance. “Each standard devia-tion higher plasma level for these vitamins predicted a global cognitive score 0.28 standard deviations better,”the researchers reported. Which value are the researchersinterpreting in this statement?A) the correlation coefficient between plasma level andcognitive scoreB) the y-intercept of the regression model predictingcognitive score from plasma levelC) the slope of the regression model predicting cognitivescore from plasma levelD) the standard deviation of the regression model’sresidualsE) R2for the regression model
An investigation of the relationship between traffic flow (measured in cars per day) and lead content (measured in micrograms per gram of dry weight) in the bark of trees near the highway yielded the following summary statistics: Sample Mean Sample Standard Deviation Lead Content (micrograms per gram dry weight) y¯=y¯= 680 sysy = 240 Traffic Flow (cars / day) x¯=x¯= 1750 sxsx = 800 The correlation between lead content and traffic flow was found to be r = 0.6 and a scatterplot showed the form to be linear. Since Traffic flow is the X-variable, its mean and standard deviation have been labelled x¯ and sxx¯ and sx. Since Lead content is the Y-variable, its mean and standard deviation have been labelled y¯ and syy¯ and sy . Determine slope and y-intercept of the least squares regression line for using X to predict Y. Group of answer choices Slope y-intercept
Albumin is a liver protein that helps with circulation of hormones, vitamins, and enzymes throughout our body. Reduced albumin concentrations have been associated with severe liness among individuals infected with COVID-19. Suppose we wanted to conduct a study to compare the mean Albumin concentration (gL) between a sample of adult patients hospitalized at MUSC for COVID-19 infection (g=32.8, s-6.0) to the mean Albumin concentration (gL) of healthy U.S. adults (u-34.1, os7.13). How many patients would we need to enroll from MUSC to conduct this study with 95% confidence, and 90% power? From: Chen T, Wu D, Chen H, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study (published correction appears in BMJ. 2020 Mar 31;368.m 1295). BMJ. 2020;368:m1091. Published 2020 Mar 26. doi:10.1136/bmj.m1091 O 269 O 164 O 292 O 316
24) Below is some of the regression output from a simple regression of the number of wins for a major league baseball team and the size amount of money the team is paying its players (expressed in millions of $'s) *fill in blanks of the table* Based on the regression output, what is the correlation between the two variables? *round to 3 decimal places*

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