FORE SCHOOL OF MANAGEMENT

Project To understand the significant

difference between variables of two different food providing agencies

Business Research Methods

Neelutpal Saha

Roll No-222012

Introduction

A t-test is any statistical hypothesis test in which the test statistic follows a t distribution if the

null hypothesis is supported. It can be used to determine if two sets of data are significantly

different from each other, and is most commonly applied when the test statistic would follow a

normal distribution if the value of a scaling term in the test statistic were known.

There are three methods of t-test

One-sample t-test

Paired sample t-test

Independent sample t-test

The Paired-Samples T Test procedure compares the means of two variables for a single group.

The procedure computes the differences between values of the two variables for each case and

tests whether the average differs from 0.

The Test Statistic

The test statistic in either case is t. Here is the formula for t.

M is the sample mean and μ0 is the hypothetical mean. For a paired-samples t-test, M is the

mean of the difference scores and μ0 is 0. SD is the standard deviation (of the difference scores

in the case of a paired-samples t-test) and N is the number of subjects in the sample.

The p Value

p is the probability of getting a t value at least as extreme as the one we get if the null hypothesis

were true. When doing t-tests by hand, however, we typically do not figure out the exact p

value. Instead, we just figure out whether or not p is lower than your criterion for deciding

whether or not our t value is extreme or unusual. This is our α level, which is usually set to 5%

(sometimes expressed as .05).

Data: For each paired test, we specify two quantitative variables (interval level of measurement

or ratio level of measurement). For a matched-pairs or case-control study, the response for each

test subject and its matched control subject must be in the same case in the data file.

Assumptions: Observations for each pair should be made under the same conditions. The mean

differences should be normally distributed. Variances of each variable can be equal or unequal.

Test Case

We are testing our assumption on two eataries: Dunkin Donuts and McDonalds

Dunkin' Donuts is an American global doughnut company and coffeehouse chain based in

Canton, Massachusetts. It was founded in 1950 by William Rosenberg in Quincy, Massachusetts.

Since its founding, the company has grown to become one of the largest coffee and baked goods

chain in the world, with 15,000 restaurants in 37 different countries. The chain has grown to

include over 1,000 items on their menu, including doughnuts, bagels, other baked goods, and a

wide variety of hot and iced beverages. In NCR region, Dunkin Donuts has more than 20 food

stations.We are testing the food for Dunkin Donuts in Cyber City Gurgaon

The McDonald's Corporation is the world's largest chain of hamburger fast food restaurants,

serving around 68 million customers daily in 119 countries across 35,000 outlets.Headquartered

in the United States, the company began in 1940 as a barbecue restaurant operated by Richard

and Maurice McDonald. McDonald's primarily sells hamburgers, cheeseburgers, chicken, french

fries, breakfast items, soft drinks, milkshakes, and desserts. In response to changing consumer

tastes, the company has expanded its menu to include salads, fish, wraps, smoothies, fruit, and

seasoned fries. McDonalds has a huge presence in Delhi NCR region, we are testing the food for

Cyber City Gurgaon division.

A questionnaire consisting of 10 questions each based on the following parameters was prepared:

Taste

Menu Variety

Cost

Quality of Ingredients

Hygiene

Service quality

Ambience

Nutrition

Timings at which they are open

Total time taken for the meal

The respondents for the exercise were employees from my own organization Ericsson who

freqented both spots as they are nearby. The ratings on the basis of which these parameters were

judged are:

1=Extremely Unsatisfied, 2= Unsatisfied, 3= Neutral, 4 = Satisfied, 5= Extremely Satisfied

We will be using IBM SPSS Statistics tool which is a software package used for statistical

analysis

Defining the Variables and Test method

First we need to define the variables in SPSS in variable view in the following way:

Next we define the ratings given for ‘Taste’ by each respondent for Dunkin Donut (given by

Taste1) and McDonalds (given by Taste2) in the following manner:

We go to the ‘Analyze’ tab then click ‘Compare Means’ and then apply ‘Paired Samples T-test’

Outputs for each Parameters:

While comparing for each parameter;

Null Hypothesis will be Parameter of Restaurant1=Parameter of Restaurant 2

Alternate will be they are not equal to each other.

We are testing at 5% level of significance

We check for the significant value in each case, if the value is greater than 0.05 then

Null hypothesis is accepted and if it is less then it is rejected and there exists significant

difference between the two parameters

Taste

The sig value is .741, therefore Null hypothesis is accepted and there exists no

significant difference in the taste of the two restaurants.

Menu

The sig value is 1, therefore Null hypothesis is accepted and there exists no significant

difference in the menu of the two restaurants.

Cost

The sig value is .055, therefore Null hypothesis is accepted and there exists no

significant difference in the Cost of the two restaurants.

Quality

The sig value is .214, therefore Null hypothesis is accepted and there exists no

significant difference in the quality of the two restaurants.

Hygeine

The sig value is .428, therefore Null hypothesis is accepted and there exists no

significant difference in the hygeine of the two restaurants.

Service Quality

The sig value is .330, therefore Null hypothesis is accepted and there exists no

significant difference in the service quality of the two restaurants.

Ambience

The sig value is .649, therefore Null hypothesis is accepted and there exists no

significant difference in the ambience of the two restaurants.

Nutrition

The sig value is .428, therefore Null hypothesis is accepted and there exists no

significant difference in the nutrition of food of the two restaurants.

Timings

The sig value is 1.000, therefore Null hypothesis is accepted and there exists no

significant difference in the timings of the two restaurants.

Preparation Time

The sig value is .097, therefore Null hypothesis is accepted and there exists no

significant difference in the prepartion time for the two restaurants.

Conclusion

S. No. Parameters Significant Statistical Difference

1 Taste No

2 Menu Variety No

3 Cost No

4 Quality of Ingredients No

5 Hygiene No

6 Service quality No

7 Ambience No

8 Nutrition No

9 Timings at which they are open No

10 Total time taken for the meal No