Understanding Test Statistics
A test statistic is a standardized value computed from sample information when testing hypotheses. It compares the given data with what an analyst would expect under the null hypothesis. As such, it is a major determinant when deciding whether…
Understanding the Decision Rule
The decision rule refers to the procedure followed by analysts and researchers when deciding whether to reject or not to reject a null hypothesis. We use the phrase “not to reject” because it is considered statistically incorrect to “accept”…
Statistical Result vs. Economically Meaningful Result
Statistical significance refers to the use of a sample to carry out a statistical test meant to reveal any significant deviation from the stated null hypothesis. We then decide whether to reject or not to reject the null hypothesis. Economic…
The p-value in Hypothesis Testing
The p-value is the lowest level of significance at which we can reject a null hypothesis. It is the probability of coming up with a test statistic that would justify our rejection of a null hypothesis, assuming that the null…
Uses of the t-test and the z-test
The z-test The z-test is the ideal hypothesis test to conduct in a normal distribution of a random variable. In addition, the variance of the population must be known. The z-statistic refers to the test statistic computed for hypothesis testing.
Difference Between Two Population Means
It is common for analysts to establish whether there is a significant difference between the means of two different populations. For instance, they might want to know whether the average returns for two subsidiaries of a given company exhibit a…
Chi-square Test of a Single Population Variance and F-test of the Ratio of Two Population Variances
Testing the Variances of a Normally Distributed Population using the Chi-square Test A chi-square test is used to establish whether a hypothesized value of variance is equal to, less than, or greater than the true population variance. Unlike most distributions…
Parametric vs. Non-Parametric Tests
Parametric Tests Parametric tests are statistical tests in which we make assumptions regarding population distribution. Such tests involve the estimation of the key parameters of a distribution. For example, we may wish to estimate the mean or compare population proportions….
Technical Analysis (TA)
Technical analysis is the practice of using price and volume data to value stocks. It upholds the idea that supply and demand, that jointly constitute market forces, ultimately determine the stock price. Technical analysis is a concept widely used to…
