ASSIGNMENT 1
EBC2170 Business Research methods for Premaster
Introduction
With entering the last phase of the COVID pandemic, a large service company—which has several hubs
around the globe—wants to get insight into how sales and consumer satisfaction are influenced by
whether the service personnel is wearing facemasks or not.
Description dataset
A survey was conducted among 100 customers. The following data was collected for each customer:
Information on whether the customer was served by an employee wearing a face mask (MASK =
1) or not (MASK = 0);
Information on the amount of money spent by that particular customer (SALES);
Information on customer satisfaction as measured by the customers’ agreement to the following
3 scale items, all measured on an 7-point Likert scale (1 = completely disagree, 7 = completely
agree):
1. “I found the interaction with the employee satisfactory.” (SATIS1)
2. “I am satisfied with the service that I bought.” (SATIS2)
3. “I would NOT recommend this company to a friend.” (SATIS3)
Information on the GENDER of the customer
Information on the quality of the employee (on a scale ranging from 1: extremely bad quality to
15: extremely good quality) that served that particular customer (QUAL)
Questions
1. Identify the key dependent and independent variable(s), state whether they are categorical or
continuous variables, and formulate the null hypotheses.
Dependent variables:
customer satisfaction (continuous, interval) and sales (continuous, ratio). NOTE: In consumer
psychology, we treat seven-point scales as interval measurements. This makes your life a lot easier
as it allows you to conduct substantially more analyses than when it would be considered to be
ordinal.
Independent variables:
mask (categorical, nominal)
Null hypotheses:
H0: The personnel wearing a mask or not does NOT influence sales.
H0: The personnel wearing a mask or not does NOT influence customer satisfaction.
1
, 2. Create a new variable SATIS3REV where the answers to SATIS3 are reverse coded. Use the “recode
into different variables” function to do this.
RECODE SATIS3 (1=7) (2=6) (3=5) (4=4) (5=3) (6=2) (7=1) INTO SATIS3REV.
EXECUTE.
3. Create a new variable SATIS, that averages the scores of the four scale items: SATIS1, SATIS2,
SATIS3REV. Use the “compute” function to do this.
COMPUTE SATIS=MEAN(SATIS1,SATIS2,SATIS3).
EXECUTE.
4. Compute and interpret descriptive statistics (mean, median, mode, st. dev., min., max.) of the
following variables: SALES, SATIS, and QUAL. Do it for the sample as a whole, and also for both groups
of customers (i.e., group 1 has MASK = 0 and group 2 has MASK = 1). Also check how many customers
were in the MASK = 0 and MASK = 1 group, and how many male and female customers were included
in the dataset. Were there any missing observations for each of the variables?
NOTE: it is best to use the following pathway in SPSS to retrieve descriptive stats: Analyze >
Descriptive Statistics > Frequencies.
FOR THE DATASET AS A WHOLE:
FREQUENCIES VARIABLES=SALES SATIS QUAL
/STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIAN MODE
/ORDER=ANALYSIS.
2
EBC2170 Business Research methods for Premaster
Introduction
With entering the last phase of the COVID pandemic, a large service company—which has several hubs
around the globe—wants to get insight into how sales and consumer satisfaction are influenced by
whether the service personnel is wearing facemasks or not.
Description dataset
A survey was conducted among 100 customers. The following data was collected for each customer:
Information on whether the customer was served by an employee wearing a face mask (MASK =
1) or not (MASK = 0);
Information on the amount of money spent by that particular customer (SALES);
Information on customer satisfaction as measured by the customers’ agreement to the following
3 scale items, all measured on an 7-point Likert scale (1 = completely disagree, 7 = completely
agree):
1. “I found the interaction with the employee satisfactory.” (SATIS1)
2. “I am satisfied with the service that I bought.” (SATIS2)
3. “I would NOT recommend this company to a friend.” (SATIS3)
Information on the GENDER of the customer
Information on the quality of the employee (on a scale ranging from 1: extremely bad quality to
15: extremely good quality) that served that particular customer (QUAL)
Questions
1. Identify the key dependent and independent variable(s), state whether they are categorical or
continuous variables, and formulate the null hypotheses.
Dependent variables:
customer satisfaction (continuous, interval) and sales (continuous, ratio). NOTE: In consumer
psychology, we treat seven-point scales as interval measurements. This makes your life a lot easier
as it allows you to conduct substantially more analyses than when it would be considered to be
ordinal.
Independent variables:
mask (categorical, nominal)
Null hypotheses:
H0: The personnel wearing a mask or not does NOT influence sales.
H0: The personnel wearing a mask or not does NOT influence customer satisfaction.
1
, 2. Create a new variable SATIS3REV where the answers to SATIS3 are reverse coded. Use the “recode
into different variables” function to do this.
RECODE SATIS3 (1=7) (2=6) (3=5) (4=4) (5=3) (6=2) (7=1) INTO SATIS3REV.
EXECUTE.
3. Create a new variable SATIS, that averages the scores of the four scale items: SATIS1, SATIS2,
SATIS3REV. Use the “compute” function to do this.
COMPUTE SATIS=MEAN(SATIS1,SATIS2,SATIS3).
EXECUTE.
4. Compute and interpret descriptive statistics (mean, median, mode, st. dev., min., max.) of the
following variables: SALES, SATIS, and QUAL. Do it for the sample as a whole, and also for both groups
of customers (i.e., group 1 has MASK = 0 and group 2 has MASK = 1). Also check how many customers
were in the MASK = 0 and MASK = 1 group, and how many male and female customers were included
in the dataset. Were there any missing observations for each of the variables?
NOTE: it is best to use the following pathway in SPSS to retrieve descriptive stats: Analyze >
Descriptive Statistics > Frequencies.
FOR THE DATASET AS A WHOLE:
FREQUENCIES VARIABLES=SALES SATIS QUAL
/STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIAN MODE
/ORDER=ANALYSIS.
2
