In the following exercise, visually check the conditions for fitting a least squares regression line, but you do not need to report these conditions in your solutions.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.6020-20Husband's age (in years)4060Given below is summary output of the least squares fit for predicting wife's age from husband's age.EstimateStd. Errort valuePr(>|t|)(Intercept)1.57401.15011.370.1730age_husband0.91120.025935.250.0000df == 168= 1. Use the information(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 ß,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. Since df168, the p-value is between 0.020 and 0.010 vXTherefore, the data%3Dprovidestrong evidence that the average difference between husbands' and wives' ages differs for different ages.(b) Write the equation of the regression line for predicting wife's age from husband's age. (Enter your answers to four decimal places.)agewx ageH+%D(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 additionalyears 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 averageyears old.Wife's age (in years)

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Description: In the following exercise, visually check the conditions for fitting a least squares regression line, but you do not need to report these conditions in your solutions.The scatterplot below displays the relationship between husbands' and wives' ages

(a)Using the given point estimate and standard error, we can compute a T score of 35.25. Since df =…

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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 Wife's age (in years)

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 Wife's age (in years)

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Concept explainers

Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.

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Question

In the following exercise, visually check the conditions for fitting a least squares regression line, but you do not need to report these conditions in your solutions.
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
20-
20
Husband's age (in years)
40
60
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(>|t|)
(Intercept)
1.5740
1.1501
1.37
0.1730
age_husband
0.9112
0.0259
35.25
0.0000
df =
= 168
= 1. Use the information
(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 ß,
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
. Since df
168, the p-value is between 0.020 and 0.010 vX
Therefore, the data
%3D
provide
strong evidence that the average difference between husbands' and wives' ages differs for different ages.
(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 ageH
+
%D
(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.
Wife's age (in years)

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