## Introduction and Statement of the Problem

## Hypothesis

## Data and Sample

## Analysis

From the analysis carried out, it is observed that the relationeship is significant. although, some variables like Age and Income are statistically significant at 10%, hence, we reject the null hypothesis and conclude that there exists a significant relationship between average amount of money spent at Starbucks per visit and income, age, gender and frequency of visit.

The chi-squared test of independence carried out reveals that there is an association between number of visit and amount spent. Hence, the null hypothesis will be rejected in favor of alternative.

Since the p-value (0.3279) is greater than the significance level (0.5), we do not reject the null hypothesis and conclude that there is no significant difference in the amount spent among the male female customers.

Analysis of variance table above reveals that there are there is no significant difference in the amount spent among the age brackets since the p-value is more than the significance level (0.05). hence, we do not reject the null hypothesis.

##### Limitation and recommendation

So much information is lost in the data as a result of grouping into category done on most of the variables and this can lead to reduction in precision. Also, non-parametric approach should be adopted in the analyses sincedistributional assumptions in parametric approach will not be met.