Question

Q2. Now that you know the answer to the above question, you decide that you want to predict the amount of trash that all of them can pick up. You find strong correlations between certain data points and trash collected, and you want to develop a predictive model to see the result. Use the attached data (Trash data) to forma multiple regression model, and explain the usefulness of the model. Use the analysis tool in Excel to calculate the model (use regression). Your Y data is the lbs of trash, and your x data is everything else. Play with some of the checkboxes as well to see what the program will do. Again, explain your result, and why it is important…

Lbs processed	Workers	animal weight	knives	hours
200	8	100	10	25
156	5	80	8	33
145	5	100	8	25
178	6	90	8	26
135	4	80	8	28
167	4	90	8	44
179	8	90	8	22
213	9	100	11	25
233	9	140	12	25
188	5	90	11	33
180	7	90	12	30
199	6	90	12	28
223	8	130	12	22
221	7	100	11	31
267	9	140	11	31
278	11	160	15	25
145	7	80	8	20
177	5	100	8	30
179	6	90	9	25
177	6	90	6	26
167	5	80	7	31
100	3	70	3	34
99	3	80	3	28
29	1	70	2	22
299	14	150	15	27
137	5	80	11	27
186	7	90	12	26
191	7	90	9	27
231	9	120	12	26
211	11	120	9	19
214	12	100	9	22
300	15	150	19	22
111	6	50	8	18
199	5	100	5	44
187	4	100	8	33

Answer 1

Firstly add data in Excel sheet and go to data analysis >regression

REGRESSION LINE IS..

Lbs process=-65.0239+9.7130*workers+0.7060*animal weight +4.0769*knives+2.7417*hours

From this regression line we can predict value of Lbs process by changing workers ,animal weight,knives and hours.

R square=93.20%

Around 93% of the variability in the variables is explained by the regression model.