Sampling Considerations and 5 Common Biases in Sampling
Sampling considerations refer to the desirable characteristics that should always be taken into account when selecting a sample so as to increase chances of accurate estimation of population parameters. In general, larger samples are preferred to smaller ones because the…
Hypothesis Testing
A hypothesis is an assumptive statement about a problem, idea, or some other characteristic of a population. It can also be considered an opinion or claim about a given issue. Therefore, a statistical test has to be performed to establish…
One-tailed vs. Two-tailed Hypothesis Testing
A one-tailed test (one-sided test) is a statistical test that considers a change in only one direction. In such a test, the alternative hypothesis either has a < (less than sign) or > (greater than sign), i.e., we consider either…
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…
