Statistical Significance is a measure of the likelihood that a true value will be represented by the average of a set of measurements. The higher the number of measurements and the closer the measured values, the higher the statistical significance. The purpose of this measure is to quantify the reliability of results from statistical tests.
Statistical significance is determined by taking the ratio of the observed effect to the expected effect. The higher the ratio, the more statistically significant the result. Generally, a result is considered statistically significant if it has a ratio of 3 or higher.
When looking at statistical significance in marketing research, it is important to consider both the practical and statistical significance of the results. Practical significance refers to the practical implications of the results, while statistical significance refers to the likelihood that the results are due to chance.
For example, imagine that you are testing a new marketing campaign and you find that it generates a 5% increase in sales. This result may be statistically significant, but if the increase in sales is only $100, it may not have much practical significance. On the other hand, if the campaign generates a 5% increase in sales and the company makes $1 million in sales, the result is both statistically and practically significant.
It is important to consider both practical and statistical significance when interpreting results from marketing research. However, statistical significance is usually given more weight than practical significance, since it is a more objective measure.
Overall, statistical significance is a helpful measurement used to quantify the reliability of results from statistical tests.
Statistical significance can be calculated using a variety of methods, such as the t-test, chi-square test, and z-test. Each method has its own advantages and disadvantages, so it’s important to understand which one best suits your needs before making any decisions.
When something is statistically significant, it means that there is a high probability that the observed result or relationship was caused by something other than chance. This means that the results are unlikely to be due to random fluctuations in data or other factors unrelated to the experiment itself.
Fun Fact:
"Statistical significance is a key concept in marketing research, as it helps to determine whether the results of a study are due to chance or if they reflect a real difference between two or more groups." According to the American Marketing Association (AMA), statistical significance is “the probability that the observed relationship between two variables would not occur by chance alone” (AMA, 2017).