In: Statistics and Probability
| 
 Cheddar cheese, total  | 
|||||
| 
 Supply and disposition2  | 
 September 2019  | 
 October 2019  | 
 November 2019  | 
 December 2019  | 
 January 2020  | 
| 
 Tonnes  | 
|||||
| 
 Supply, total  | 
 52,295  | 
 56,466  | 
 57,389  | 
 56,675  | 
 57,238  | 
| 
 Beginning stocks  | 
 39,478  | 
 41,949  | 
 44,234  | 
 42,674  | 
 42,274  | 
| 
 Production  | 
 12,407  | 
 13,808  | 
 12,474  | 
 13,388  | 
 14,738  | 
| 
 Imports  | 
 410  | 
 709  | 
 680  | 
 613  | 
 226  | 
| 
 Ending stocks  | 
 41,949  | 
 44,234  | 
 42,674  | 
 42,274  | 
 42,660  | 
| 
 Disappearance, total  | 
 10,346  | 
 12,232  | 
 14,714  | 
 14,401  | 
 14,578  | 
| 
 Exports  | 
 121  | 
 256  | 
 367  | 
 191  | 
 487  | 
| 
 Domestic disappearance  | 
 10,226  | 
 11,976  | 
 14,347  | 
 14,209  | 
 14,091  | 
| 
 Cheddar cheese, total  | 
|||||
| 
 Supply and disposition2  | 
 September 2019  | 
 October 2019  | 
 November 2019  | 
 December 2019  | 
 January 2020  | 
| 
 Tonnes  | 
|||||
| 
 Supply, total  | 
 52,295  | 
 56,466  | 
 57,389  | 
 56,675  | 
 57,238  | 
| 
 Beginning stocks  | 
 39,478  | 
 41,949  | 
 44,234  | 
 42,674  | 
 42,274  | 
| 
 Production  | 
 12,407  | 
 13,808  | 
 12,474  | 
 13,388  | 
 14,738  | 
| 
 Imports  | 
 410  | 
 709  | 
 680  | 
 613  | 
 226  | 
| 
 Ending stocks  | 
 41,949  | 
 44,234  | 
 42,674  | 
 42,274  | 
 42,660  | 
| 
 Disappearance, total  | 
 10,346  | 
 12,232  | 
 14,714  | 
 14,401  | 
 14,578  | 
| 
 Exports  | 
 121  | 
 256  | 
 367  | 
 191  | 
 487  | 
| 
 Domestic disappearance  | 
 10,226  | 
 11,976  | 
 14,347  | 
 14,209  | 
 14,091  | 
What is the anova table and multiple regression?
The attached table is an 8x5 table :
ANOVA table tests the significance of supply methods on production of cheddar cheese across 5 months
Equation formation :
Yijk = µ + ri + cj + eijk
ri is the ith row effect (supply)
cj is the jth col effect (months )
ANOVA table is used to perform multiple t-tests to test the effect of 8 different supply methods to quantity of cheddar production
Looks like :
| Source | Degrees of freedom | SS | MSS | Fratio | 
| Rows | 7 | SSR | SSR/7=MSR | MSR/MSE | 
| Columns | 4 | SSC | SSC/4=MSC | MSC/MSE | 
| Error | 28 | SSE | SSE/28=MSE | |
| Total | 39 | SST | 
However Multiple regression (I am assuming is linear ), Is used to predict the cheddar cheese value in tonnes for next month (Feb 2020) .
Multiple regression table will look like :
| Estimate | Std error | T-value | Pr(>|t|) | |
| Intercept | ||||
| Supply total | ||||
| Begining stocks | ||||
| Production | ||||
| Imports | ||||
| Ending stocks | ||||
| Disapprearence | ||||
| Exports | ||||
| Domestic Disappearence | 
Usage of F test and T test is the differenential and deciding point . while p value and hypothesis formation is also different in both these methods.