Question

1. Using bakery.xsls to exam the effect of promotion on the sales of pies (how does promotion afect the sales) ?

Date

Cakes

Pies

Cookies

Smoothies

Coffee

promotion

12/15/2015	107	60	444	174	272	none
12/16/2015	77	48	598	155	419	none
12/17/2015	65	54	638	107	341	none
12/18/2015	103	63	402	154	327	none
12/19/2015	148	76	589	168	439	none
12/20/2015	106	62	657	151	477	none
12/21/2015	73	46	570	156	238	none
12/22/2015	103	53	420	134	420	none
12/23/2015	72	44	505	156	375	none
12/24/2015	87	46	564	237	405	none
12/25/2015	90	37	838	240	581	none
12/26/2015	113	46	445	255	488	none
12/27/2015	136	49	700	265	483	none
12/28/2015	77	45	605	69	408	none
12/29/2015	93	56	508	185	452	none
12/30/2015	62	28	458	141	356	none
12/31/2015	65	56	491	190	446	none
1/14/2013	96	48	585	194	573	promotion
2/13/2013	93	61	599	218	388	promotion
2/15/2013	67	50	730	195	523	promotion
2/18/2013	84	56	549	179	320	promotion
2/21/2013	94	45	632	260	200	promotion
3/2/2013	120	84	597	247	506	promotion
3/3/2013	122	52	679	139	506	promotion
3/17/2013	117	57	718	269	440	promotion
4/8/2013	95	54	594	147	282	promotion
5/22/2013	77	68	611	145	506	promotion

Answer 1

to examine the effect of promotion on sale of pie, the days on which promotion is not done is coded as 0 and days on which promotion is done is coded as 1.

To study the impact of promotion of sale of pie, correlation and regression can be used.

Results of correlation co-efficient reveal that two variables are weakly correlated. The co-efficient of correlation is 0.276, therefore, there is weak correlation between promotion and sales.

Results of regression analysis reveal that one unit increase in promotion increases sales by 0.076 units.

It can be concluded that promotion has not impacted sale of pie in a substantial way.

Correlations
		VAR00001	VAR00002
VAR00001	Pearson Correlation	1	.276
	Sig. (2-tailed)		.163
	N	27	27
VAR00002	Pearson Correlation	.276	1
	Sig. (2-tailed)	.163
	N	27	27

IN this table variable 1 is sales and variable is promotion.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.276a	.076	.039	11.14319
a. Predictors: (Constant), VAR00002

THe table shows regression results