An industry study was recently conducted in which the sample correlation between units sold and marketing expenses was 0.64.The sample size for the study included 18 companies. Based on the sample results, test to determine whether there is a significant positive correlation between these two variables. Use α=0.01. Use t-distribution table. Answer parts a.,b. & c. a. What are the appropriate null and alternative hypotheses to test for a positive correlation? A. H0:ρ≥0 HA: ρ<0 B. H0: ρ=0 HA:ρ≠0 C. H0:ρ≤0 HA:ρ>0 D. H0:ρ<0 HA:ρ≥0 E. H0:ρ>0 HA:ρ≤0 F.H0:ρ≠0 HA:ρ=0 b. Calculate the t-test statistic for correlation t=____ (Round to four decimal places as needed) c. Determine the critical value(s) for the rejection region for the test statistic t. Select the correct choice below and fill in the answer box to complete your choice. (Round to four decimal places as needed.) A. t0.01= - _____ B. t0.01= _____ C. t0.01= ± _____ Since the test statistic _____ in the rejection region. ______ the null hypothesis. The data ______ support the contention that there is a correlation between units sold and marlketing expenses.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
between these two variables. Use α=0.01.
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