Sampling and Data Collection Plan 3

SAMPLING AND DATA COLLECTION PLAN 3

Sampling and Data Collection Plan

Latisha Hence

QNT/561

2/20/2016

Professor Robert Kalle

Introduction

Team C is using a random sampling for the research project for the Reeds Supermarket. Independent variable is the Sales Revenue and the dependent variable being types of promotion. The research question the team posed is how promotion techniques affect sales revenue does. Does promotion increase or decrease sales revenue.

Population

The research will focus on the stores that offer multiple services and the population will be 1000 stores found in Michigan. Stores use promotions to increase their sales revenue. Some stores have different type of promotions such as Social media, branding, or bundling. A shopper may decide to purchase an item depending on what type of promotion is enticing to them. Depending on the promotion the customer’s thoughts on purchasing the product will be altered. We decided to use a systematic random sampling to choose a representative sample. It has been determined to evaluate 1000 stores to see how many customers choose to buy a product depending on the promotion. The supermarket was polled for customers that choose a product on promotion, and off promotion. For an example, out of 250 people (12%) did not choose the promotion item while 88% did. If we choose a confidence interval of 95% so z = 1.96.

Data Collection

We can collect the data and compose it using systematic random sampling. The population are the customers that are shopping in Reeds Market. The sample size is 25 shoppers. Random shoppers will be chosen, based on the number of customers that enter a store at a time. A product x will be selected and placed on promotion for 15 days and off promotion for 15 days. During the 30 day period how many people chose the product x on promotion and how many people chose the product x off promotion. The sampling fraction tells us we need to sample 4 out of every 1000 customers. Using a random number table we can assign numbers to the customers and determine if they pick the product based on its promotion. Random numbers can now be added to the remaining customers. “The aim of the systemic random sample is to reduce the potential for human bias in the selection of cases to be included in the sample. As a result, the systemic random sample provides us with a sample that is highly representative of the population being studied, assuming that there is limited missing data (Lund, 2012).”

Validity and reliability will be achieved because the shoppers can be viewed on the surveillance tape to ensure the identified customers actually picked the promotion item compared to the same item not on promotion. This method will ensure shoppers natural habits are reviewed and not influenced by the study.

In our case, margin of error ME = 0.05/2

Z-score = 1.96

P1 = 0.12;

Therefore,

0.025 = 1.96√0.12 (1-0.12)/n

(0.025/1.96)2 = (0.12*0.88)/n

N = 0.21/ (0.025/1.96)2

N = 0.8235

Reference

Lund (2012). Systematic random sampling. Retrieved from, http://dissertation.laerd.com/systematic-random-sampling.php#step2