Nature and Role of Marketing Analysis (Byte Size)
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Nature and Role of Marketing Analysis (Byte Size)

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The analysis of the market is an important part of any overall evaluation or implementation of a marketing strategy. The techniques employed by analysts can be used to assess the correct marketing mix, changing market structures, support or reject hypotheses that have been proposed and forecasting or estimating market potential, to name but a few. This course looks at the differences within data, the range of data that can be encountered in marketing analysis and some of the main techniques used in the evaluation of such data.

A marketing analyst makes use of a wide selection of techniques from the quantitative methods in order to explain the market, forecast elements of the market and support management and corporate decision making.

The course will examine techniques from the quantitative methods which find widest use in the analysis of markets, such as hypothesis testing, which can be used to examine data and statistics from samples with a view to supporting or rejecting assumptions about the market population. Regression and correlation will be examined as techniques that can be employed to assess the existence and strength of relationships within a market and also their use as a possible forecasting tool. Finally, an introduction will be made to a range of multivariate techniques, which have found widest use in marketing analysis in the analysis of data from questionnaires. It is quite common to link the multivariate methods to enrich analyses. The section covering these methods will make use of a case study to demonstrate this.

Modern approaches to analysis make wide use of questionnaires to obtain primary data and computer software to analyse data. The first section of this course will therefore introduce different types of data and the approaches to coding data for analysis. There exists a wide range of statistical packages to analyse data; probably the most widely used package in the UK is Statistical Package for Social Sciences (SPSS), which has been used to facilitate analyses for this course.

By the end of this course you should be able to:

Section 1

  • Explain the use and application of variables.
  • Distinguish between the different principal types of variables.
  • Explain and identify four categories of data measurement.
  • Understand the procedures for coding data.
  • Distinguish between the methods of summarising data using location and dispersion measures.

Section 2

  • Calculate a standard Z score.
  • Set up a confidence interval with known parameters.
  • Appreciate what is meant by an hypothesis and understand the difference between a null hypothesis and an alternative hypothesis.
  • Undertake an hypothesis test and appreciate the importance of significance in hypothesis testing.
  • Undertake a chi-square test on two-dimensional data (hypothesis on non- parametric data).

Section 3

  • Understand the nature of bivariate data and straight-line relationships.
  • Measure the strength of linear relationships between variables using coefficients of correlation and determination.
  • Determine a least squares regression equation and line.
  • Estimate and forecast future data values using technique of interpolation and extrapolation.
  • Be familiar with one approach to the analysis of a time series set of data.

Section 4

  • Explain the concept of multivariate analysis in marketing.
  • Describe the application and use of a range of multivariate methods as individual techniques.
  • Describe the application and use of a range of multivariate techniques linked in an analysis.
  • Interpret printouts from a statistical package (SPSS).