Are nursing salaries in City A lower than those in City B? As reported by a newspaper, salary data show staff nurses in City A earn less than staff nurses in City B. Suppose that in a follow-up study of 40 staff nurses in City A and 50 staff nurses in City B you obtain the following results. Assume population variances are unknown and unequal. City A City B n = 40 n2 = 50 X, = $56,600 X2 = $59,500 s, = $6,000 S2 = $7,000 (a) Formulate hypotheses so that, if the null hypothesis is rejected, we can conclude that salaries for staff nurses in City A are significantly lower than for those in City B. Use a = 0.05. Ho: H1 - 42 # 0 Hại Hy - H2 = 0 Hoi H - H2 = 0 H3: H1 - 42 < 0 Ho: H1 - 42 > 0 H3: H1 - H2 = 0 Ho: H1 - H250 H3: H1 - 42 > 0 Ho: H1 - 42 < 0 Ha: H1 - 42 * 0 (b) What is the value of the test statistic? (Round your answer to three decimal places.) (c) What is the p-value? The degrees of freedom for this test are 87. (Round your answer to four decimal places.) p-value = (d) What is your conclusion? Do not Reject Ho. There is sufficient evidence to conclude that the salaries of staff nurses are lower in City A than in City B. O Reject Ho: There is sufficient evidence to conclude that the salaries of staff nurses are lower in City A than in City B. O Do not reject Ho. There is insufficient evidence to conclude that the salaries of staff nurses are lower in City A than in City B. O Reject Ho. There is insufficient evidence to conclude that the salaries of staff nurses are lower in City A than in City B.

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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.