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Correlation

Significant correlation between women's age and women's weight

Sample size, n: 40 Degrees of freedom: 38 Correlation Results: Correlation coeff, r: 0.5630033 Critical r: ±0.3120061 P-value (two-tailed): 0.00016 Reject the Null Hypothesis Sample provides evidence to support linear correlation Regression Results: Y= b0 + b1x: Y Intercept, b0: 89.71354 Slop

correlation between self esteem and shyness

A researcher finds a correlation between self esteem and shyness is -0.50, which is significant for his sample. Interpret this correlation. What does a correlation coefficient tell us? Why are correlation coefficients useful when assessing reliability? What are the 2 ways in which researchers assess the reliability of th

Diversified Portfolio, Correlation, Interest and Inflation

1) A portfolio with a correlation of +1 is not a well-diversified portfolio. What must you do as an investor to structure a portfolio with negative correlation? 2) What macroeconomic variable do you believe has the greatest impact on interest rates? Inflation? Briefly explain. 3) Compare and contrast the Capital Asset Pri

Pearson and Spearman correlations with opposite signs

Give an example of two random variables (can be discrete or continuous) whose Spearman correlation is positive but whose Pearson correlation is negative. Similarly show two random variables whose Pearson correlation is positive but whose Spearman correlation is negative.

One-half of the correlation table

**See Attached Spreadsheet** This correlation table only shows one-half of the pair-wise comparisons between these five measures. For example, it shows that the correlation between the 10-year rates of growth in sales and cash flow is 0.793 but does not show the corresponding correlation between the 10-year rates of growth in c

Significance Levels for baseball data; Spearman's Rank-Order correlation

1. Refer to the baseball data for 2005 on 30 major league teams (see bottom of page). Use a Contingency Table to analyze the relationship between games won and salary. Set up a variable that divides the teams into two groups, those that had a winning season and those that did not. There are 162 games in the season, so define a w

Significance of correlation: T Test..

Correlation and Regression Use these parameters to guide me through the steps in solving this problem. Is there a correlation between the age/year of Car and the value? YEAR, YEARS OLD; VALUE (1000's) 1981, 30, 21 1986, 25, 21 1991, 20,

Coefficient and relationships for Smith's Appliances advertising budget

Smith's Appliances is evaluating its advertising budget. The owner is trying to decide if the budget needs to be altered or not. The question: Is there a positive return on the investment that is being made in advertising? What is the relationship between sales and the amount spent on advertising? The owner collected data for th

Correlation coefficient & Margin of Error

Calculate the correlation of the data set (3,2), (3,3), (6,4). A 95% confidence interval for the average miles per gallon for all cars of a ginven type is 32.1 plus/minus 1.8. The interval is based on a sample of 40 randomly selected cars. What units represent the margin of error? Suppose you want to decrease the margin of

Correlation

Would the correlation between x and y in the table above be positive or negative? - Find the missing value of y in the table. - How would the values of this table be interpreted in terms of linear regression? - If a 'line of best fit' is placed among these points plotted on a coordinate system, would the slope of

SPSS Exercise: Correlation, Regression, Discriminant analysis

See attached file. SPSS Exercise Questions If you know how to operate SPSS, the assignment is fairly simple. The instructions are long, because I have included the scenarios as well. All datasets will be automatically entered into the SPSS by access the link below. I just need the measures ran and a synopsis to show class

Conclusion of linear correlation between education and income

Describe the error in the stated conclusion. Given: There is a linear correlation between annual personal income and years of education. Conclusion: More education causes a person's income to rise. Choose the correct answer below. A. the error in the stated conclusion is that if there is no linear correlation, there

Correlation between two variables: College GPA vs High School GPA

See attached file. How to find the correlation between two variables and how strong the relationship is and describe the conclusions and reasoning. Find the linear regression equation and if the regression equation should be used for predictive purposes College GPA High School GPA 1.72 28 2.61 3.51 25 3.66 2.45 21 3.24

Comparing Coefficients in Regression Analysis

In multiple regression, the relative size of the coefficients is not important. For example, your company may have a nationwide hiring program that focuses on hiring employees who have graduated from college in the past 3 years, and let's say you want to know what attributes of those graduates has the biggest influence on sales

Correlation Matrix: Interpret Data for JAX, DFW, & LAX Models

See attached files. Provide a correlation matrix. Use the data to obtain the 'best' multiple regression model. Can you please provide a short write-up in Word that interprets your output discussing - which independent variables are most strongly related to price, - which are least strongly related to price,

Provide explanations for each of the correlations

Explanation A.) Regression and correlation are the most used and most abused tools in research. People are often quick to jump to the conclusion that if a relationship exists between two variables, one must cause the other. In reality, there are many reasons why two variables can be related without causality. Give a plausi

Statistics: High correlation between average annual wages and US GNP

Please give your best opinion as needed. In many business and economics applications, we may observe highly correlated variables when each pair of observations corresponds to a particular time period. For example, we would expect a high correlation between average annual wages and the U.S. gross national product (GNP) whe

Correlations of Spending vs Saving, Street cops vs Crime

Give a plausible explanation for the following correlations: a. There is a strong relationship between the amount of money people spend and the amount people save (in other words, people who spend more tend to save more). Does this mean that you can improve your life savings by spending more money? Explain how this correlatio

Multiple choice questions with correlation coefficient

Which of the following statements about the correlation coefficient is incorrect: 1.) 0 <=r<=1 2.) The larger the absolute value of r the stronger the linear relationship between x and y. 3.) r = 0 implies absolutely no relationship between x and y 4.) The coefficient of determination can never be negative 5.) if b1 is

College Drinking and Poor Grades (Correlation)

How does college drinking correlate to poor grades? Please find information that would have nominal definitions and instruments, or other measurement strategies, add reliability and validity in the information you find. Please make sure it identifies the population.

Calculate and test for partial correlation

A researcher is interested in determining the partial correlation between age (X) and attitude towards interracial marriage (X), controlling for place of residence (rural or urban) (W). The researcher finds the following correlations: r sub xy=0.60; r sub xw=0.43; r sub yw=-.70, for N=175. Calculate the partial correlation co

Explaining Correlation

What does it mean to say that a correlation is "strong?" How can we assess the strength of a correlation by looking at a scatter graph of the data? A "strong" correlation is a relative term and depends on the field of study. All things being equal, correlation values above 0.90 or -0.90 can be described as "strong." Again, th

Explain how people's scores on two variables used in calculation

Determining the strength of a correlation is very important to determine how well one variable can predict another. To determine the strength of a correlation, we have to calculate the correlation coefficient, r. Explain how people's scores on two variables can be used to calculate r.