hypothesis testing is of fundamental importance for market research.

hypothesis testing is of fundamental importance for market research.

Hypothesis Testing & ANOVA - marketing research

This chapter's learning objectives

• The logic of hypothesis testing.
• The steps involved in hypothesis testing.
• What test statistics are.
• Types of error in hypothesis testing.
– Common types of t-tests, one-way and two-way ANOVA.
• How to interpret SPSS outputs.

Introduction

we use descriptive statistics to compare groups. For example, we might be interested in investigating whether men or women spend more money on the Internet. Assume that the mean amount that a sample of men spends online is $200 per year against the mean of $250 for the women sample. Two means drawn from different samples are almost always different (in a mathematical sense), but are these differences also statistically significant?

To determine statistical significance, we need to ascertain whether this finding is attributable to chance or if these findings are likely due to significant differences. If the difference is so large that it is unlikely to have occurred by chance, we call this statistical significance. Whether results are statistically significant depends on several factors, including variation in the sample data and the number of observations.

In this chapter, we will introduce hypothesis testing which allows for the determination of statistical significance. As statistical significance is a precursor to establishing practical significance, hypothesis testing is of fundamental importance for market research.

hypothesis testing is of fundamental importance for market research.