In a manufacturing process the assembly line speed (feet per minute) was thought toaffect the number of defective parts found during the inspection process. To test thistheory, managers devised a situation in which the same batch of parts was inspectedvisually at a variety of line speeds. They collected the following data.Line SpeedNumber of DefectiveParts Found20 2120 1940 1530 1660 1440 17a. Develop the estimated regression equation that relates line speed to thenumber of defective parts found.b. At a .05 level of significance, determine whether line speed and number ofdefective parts found are related.c. Did the estimated regression equation provide a good fit to the data?d. Develop a 95% confidence interval to predict the mean number of defectiveparts for a line speed of 50 feet per minute.
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.
In a manufacturing process the assembly line speed (feet per minute) was thought to
affect the number of defective parts found during the inspection process. To test this
theory, managers devised a situation in which the same batch of parts was inspected
visually at a variety of line speeds. They collected the following data.
Line Speed
Number of Defective
Parts Found
20 21
20 19
40 15
30 16
60 14
40 17
a. Develop the estimated regression equation that relates line speed to the
number of defective parts found.
b. At a .05 level of significance, determine whether line speed and number of
defective parts found are related.
c. Did the estimated regression equation provide a good fit to the data?
d. Develop a 95% confidence interval to predict the mean number of defective
parts for a line speed of 50 feet per minute.
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