Let S(t) be the retails sales in billions of dollars in t years since 1995. A linear model for the data is F(t) = 9.44t + 84.182. 220- 210- 200- 190- 180- 170 160 150 140 130 120 110- 100- 90 3. 9 12 804 Use the above scatter plot to decide whether the linear model fits the data well. O The function is not a good model for the data O The function is a good model for the data. Estimate the retails sales in the U. S. in 2017. billions of dollars. Use the model to predict the year in which retails sales will be $243 billion.
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.
Regression Analysis:
An independent variable is multiplied with a slope and added with an intercept to get the dependent variable is basically known as a regression. The estimation of the dependent variable can a good estimate if the regression model is a good fit model.
In order to know whether the model is a good fit or not, the residual has to be less.
Residual= observed value - predicted value.
e=y-.
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