The data on the production volume z and total cost y for particular manufacturing operation were used to develop the estimated regression equation ŷ = -965.69 + 10.59x. a. The company's production schedule shows that 500 units must be produced next month. Predict the total cost for next month. (to 2 decimals) ŷ* = 4,329.: b. Develop a 98% prediction interval for the total cost for next month. (to 2 decimals) (to 3 decimals) (to 2 decimals) 323.62 t-value 3.75 4746.7 Spred Prediction Interval for an individual Value next month ( 1,451 c. If an accounting cost report at the end of next month shows that the actual production cost during the month was $6,000, should managers be concerned about incurring such a D) (to whole number) 5,779 high total cost for the month? Discuss. Based on one month, $6,000 is not outside the upper limit of the prediction interval. A sequence of five to seven months with consistently high costs should cause concern.
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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