Research Methods Descriptives Essay

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NV4602 Research Methods for Postgraduate Study
Descriptive Statistics

Outline of lecture
 Purpose of descriptive statistics
 Describing categorical variables
 Frequency analysis

 Describing continuous variables
 Summary statistics
 Measures of central tendency, variability and normality

 Normal distribution

 Relevant SPSS commands:
 Descriptives, Compare means, Histograms, Explore
 Next lab session

Objectives for today
 Understand the importance of exploring the characteristics of your data before conducting the final analyses
 Appreciate why categorical and continuous data require different kinds of descriptive analysis  Identify and define key measures of:
 Central tendency, Variability, Normality

 Explore these data characteristics using various SPSS commands (next lab session)

Population and Sample
 Population
 A group of people: e.g. all students at Brunel, all employees in
Company A, all customers
 A set of objects: e.g. all cars produced by Company A in 2012
 Census
 When data is gathered from the whole population
 Sample
 Subset of the population
 Constraints
 Time
 Money
 Availability of researchers 4

Why do descriptive statistics?
 What do we need to do before we run statistical tests that will provide conclusive answers to our research questions?
 We need to get to know our data better
 A summary or overview

 What do descriptive statistics allow us to do?
 Describe the general characteristics of the sample from which the data was collected (sample/group sizes, mean age etc.)
 Check variables for violations in the assumptions underlying the statistical tests you intend to use

Categorical variables
 Examples of categorical variables?

Gender, nationality, marital status, grade, education level

 Level of measurement?

Nominal and ordinal

 It is usually valuable to know how many cases belong to each group as defined by your categorical variables 

How many cases are there in each category group?

 Most statistical tests require

roughly equal numbers of cases in each group at least 10 cases (but more = better) in all groups

 order to produce reliable results

Categorical variables
 Example research questions:

“Is the Product easy to use, attractive, etc?”, “Is website A better than website B?”, “Does working from home decrease productivity”, “Does stress increase customer defection?”

 What was the relative proportion of males and females in your sample?

Demographic information is normally reported in the method section of your report
For e.g. If this is not 50/50 then is the sample representative of the population of interest?

 You may need to collect more data

If the sample does not reflect the demographic structure of the target population
Or is otherwise unbalanced or group sizes are too small for analysis

Categorical variables
 In SPSS to obtain descriptive statistics for categorical variables, select:
 Analyse > Descriptive
Statistics > Frequencies

Examining the frequency

table for the Gender category variable.

Comparing the groups may be

problematic in this case. Why?

Categorical variables
 Frequency tables may also be sufficient to fully answer simple questions
 e.g. Running a count on responses to a question:

“Which is your favourite social media platform?”

 Could also provide a rank order of popularity
 But no test of statistical ‘significance’

(simplistic) example: in a sample of 200, 99 males and
101 females said they use Twitter.
So, can we conclude that females use Twitter more than males?  We’ll look at significance testing next session

Continuous variables
 Continuous variables are scale level measures
 e.g. Age, weight, height, time, test scores,