Automobile Sales ~ Factors Concerning Purchasing                                            SPSS Data Analysis

Contents Table

1        Introduction…………………………………………………………        ………3

2        The Sample………………………………………………………………….4

  1. Description of Data……………………………………………..…………...5
  2. Bivariate analysis of data……………………………………………………12
  3. Conclusion…………………………………………………………………..19

Bibliography & References…………………………………..


1        Introduction

A random sample of 20 car users were consulted about four factors that determined their choice of car; miles per gallon, horsepower, service interval and price.

Utilising SPSS, the subsequent report will aid in describing, manipulating, analysing and interpreting this sample of collected data. It will see if there is a relationship between variables and if one variable can predict another.

The report will be split into the following sections:

2- Display of data that is to be used in SPSS.

3- Description of data using appropriate descriptive statistics

4- Using appropriate techniques to see if there is a relationship between variables and to see if one

    can predict another.

5- The report will conclude with a summary of all the findings.

                


2        The Sample        

The following is the data drawn at random from 20 car users. The choice of car was determined by four factors- miles per gallon, horsepower, service interval and price. I will use SPSS to analyse the data for meaning.

Table 2:        Random Sample of 20 Car Users


  1. Description of Data

In order to identify which descriptive analytical tools to use I must identify the type of data being analysed. The data is Univariate as is a single set of data. This then gives way to the question what is the scale level of the variable. There are 3 possible routes here :

  • Nominal – Categorised data
  • Ordinal – Ranked data
  • Interval – collected with random answer

The data in this case is collected in interval mode as replies not categorised or given in rank but actual answers given randomly dependent on preference. Therefore using the flow chart below it can be seen that in order to do a descriptive analysis of data using interval method must first calculate mean and standard deviation then carry out either a z or t test.  

                                Interval                                                      Nominal

                                                                           Ordinal  

  1. Descriptive
  1. Central

Tendency

  1. Dispersion

2. Inferential

The table below is the descriptive analysis of the data.

The range shows the value between the minimum and maximum data number in that field this will help to show if preference is more spread i.e. wide range or concentrated i.e. small range.

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The minimum shows the least value in that specific area of preference e.g. lowest price for car.

The maximum shows the highest value for that area of preference e.g. highest car price.

The above are all measures of dispersion i.e. the spread of the data.

Saunders  et al 1997 believes “The central tendency usually provides some general impression of values that could be seen as common, middling or average.”

The mean is the most frequently use measure of central tendency and is described as the average that includes all data values in its calculation. As in the case ...

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