onsider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 3,900 450 4,900 550 5,500 600 5,900 700 6,400 750 7,100 This data was used to develop an estimated regression equation, ŷ = 970.67 + 8.08x, relating production volume and cost for a particular manufacturing operation. Use ? = 0.05 to test whether the production volume is significantly related to the total cost. (Use the F test.) Set up the ANOVA table. (Round your p-value to three decimal places and all other values to two decimal places.) Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value Regression Error Total Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value = What is your conclusion? Reject H0. We conclude that the relationship between production volume and total cost is significant.Do not reject H0. We conclude that the relationship between production volume and total cost is significant. Reject H0. We cannot conclude that the relationship between production volume and total cost is significant.Do not reject H0. We cannot conclude that the relationship between production volume and total cost is signifi
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.
Production Volume (units) |
Total Cost ($) |
---|---|
400 | 3,900 |
450 | 4,900 |
550 | 5,500 |
600 | 5,900 |
700 | 6,400 |
750 | 7,100 |
Source of Variation |
Sum of Squares |
Degrees of Freedom |
Mean Square |
F | p-value |
---|---|---|---|---|---|
Regression | |||||
Error | |||||
Total |
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