The scatterplot below displays the relationship between husbands' and wives' ages in a random sample of 170 married couples in Britain, where both partners' ages are below 65 years. 60- 40- 20 40 60 Husband's age (in years) Given below is summary output of the least squares fit for predicting wife's age from husband's age. Estimate Std. Error t value Pr(>It]) (Intercept) 1.5740 1.1501 1.37 0.1730 age_husband 0.9112 0.0259 35.25 0.0000 df = 168 (a) We might wonder, is the age difference between husbands and wives consistent across ages? If this were the case, then the slope parameter would be B, - 1. Use the information above to evaluate if there is strong evidence that the difference in husband and wife ages differs for different ages. (Round your test statistic to two decimal places.) Using the given point estimate and standard error, we can compute a T score of between husbands' and wives' ages differs for different ages. ]. -- Since df = 168, the p-value is Select v. Therefore, the data provide vv strong evidence that the average difference (b) Write the equation of the regression line for predicting wife's age from husband's age. (Enter your answers to four decimal places.) agew= x age (c) Interpret the slope in context. (Enter your answer to four decimal places.) For each additional year in husband's age, the model predicts an additional | years in wife's age. Interpret the intercept in context. (Enter your answer to four decimal places.) Men who are 0 years old are expected to have wives who are on average ] years old. [ (d) Given that R? = 0.88, what is the correlation of ages in this data set? (Round your answer to two decimal places.) (e) You meet a married man from Britain who is 55 years old. What would you predict his wife's age to be? (Round your answer to two decimal places.)
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.
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