You know what is tragic? Having the potential to complete the research study but not doing the correct hypothesis testing. Quite often, researchers think the most challenging aspect of research is standardization of experiments, data analysis or writing the thesis! But in all honesty, creating an effective research hypothesis is the most crucial step in designing and executing a research study. An effective research hypothesis will provide researchers the correct basic structure for building the research question and objectives. Show
In this article, we will discuss how to formulate and identify an effective research hypothesis testing to benefit researchers in designing their research work. Table of Contents What Is Research Hypothesis Testing?Hypothesis testing is a systematic procedure derived from the research question and decides if the results of a research study support a certain theory which can be applicable to the population. Moreover, it is a statistical test used to determine whether the hypothesis assumed by the sample data stands true to the entire population. The purpose of testing the hypothesis is to make an inference about the population of interest on the basis of random sample taken from that population. Furthermore, it is the assumption which is tested to determine the relationship between two data sets. Types of Statistical Hypothesis TestingSource: https://www.youtube.com/c/365DataScience1. There are two types of hypothesis in statisticsa. Null HypothesisThis is the assumption that the event will not occur or there is no relation between the compared variables. A null hypothesis has no relation with the study’s outcome unless it is rejected. Null hypothesis uses H0 as its symbol. b. Alternate HypothesisThe alternate hypothesis is the logical opposite of the null hypothesis. Furthermore, the acceptance of the alternative hypothesis follows the rejection of the null hypothesis. It uses H1 or Ha as its symbol
2. Depending on the population distribution, you can categorize the statistical hypothesis into two types.a. Simple HypothesisA simple hypothesis specifies an exact value for the parameter. b. Composite HypothesisA composite hypothesis specifies a range of values.
3. Based on the type of statistical testing, the hypothesis in statistics is of two types.a. One-TailedOne-Tailed test or directional test considers a critical region of data which would result in rejection of the null hypothesis if the test sample falls in that data region. Therefore, accepting the alternate hypothesis. Furthermore, the critical distribution area in this test is one-sided which means the test sample is either greater or lesser than a specific value. b. Two-TailedTwo-Tailed test or nondirectional test is designed to show if the sample mean is significantly greater than and significantly less than the mean population. Here, the critical distribution area is two-sided. If the sample falls within the range, the alternate hypothesis is accepted and the null hypothesis is rejected.
Steps in Statistical Hypothesis TestingStep 1: Develop initial research hypothesisResearch hypothesis is developed from research question. It is the prediction that you want to investigate. Moreover, an initial research hypothesis is important for restating the null and alternate hypothesis, to test the research question mathematically. Step 2: State the null and alternate hypothesis based on your research hypothesisUsually, the alternate hypothesis is your initial hypothesis that predicts relationship between variables. However, the null hypothesis is a prediction of no relationship between the variables you are interested in. Step 3: Perform sampling and collection of data for statistical testingIt is important to perform sampling and collect data in way that assists the formulated research hypothesis. You will have to perform a statistical testing to validate your data and make statistical inferences about the population of your interest. Step 4: Perform statistical testing based on the type of data you collectedThere are various statistical tests available. Based on the comparison of within group variance and between group variance, you can carry out the statistical tests for the research study. If the between group variance is large enough and there is little or no overlap between groups, then the statistical test will show low p-value. (Difference between the groups is not a chance event). Alternatively, if the within group variance is high compared to between group variance, then the statistical test shows a high p-value. (Difference between the groups is a chance event). Step 5: Based on the statistical outcome, reject or fail to reject your null hypothesisIn most cases, you will use p-value generated from your statistical test to guide your decision. You will consider a predetermined level of significance of 0.05 for rejecting your null hypothesis, i.e. there is less than 5% chance of getting the results wherein the null hypothesis is true. Step 6: Present your final results of hypothesis testingYou will present the results of your hypothesis in the results and discussion section of the research paper. In results section, you provide a brief summary of the data and a summary of the results of your statistical test. Meanwhile, in discussion, you can mention whether your results support your initial hypothesis. ConclusionNote that we never reject or fail to reject the alternate hypothesis. This is because the testing of hypothesis is not designed to prove or disprove anything. However, it is designed to test if a result is spuriously occurred, or by chance. Thus, statistical hypothesis testing becomes a crucial statistical tool to mathematically define the outcome of a research question. Have you ever used hypothesis testing as a means of statistically analyzing your research data? How was your experience? Do write to us or comment below. What test would you want to test a non directional research hypothesis?Standard textbooks on statistics clearly state that non-directional research hypotheses should be tested using two-tailed testing while one-tailed testing is appropriate for testing directional research hypotheses (e.g., Churchill and Iacobucci, 2002, Pfaffenberger and Patterson, 1987).
What type of test is nondirectional?Non-directional tests are called "two-tailed" tests because we must include the possibility that the alternative population could be less than m or greater than m. Directional or "one-tailed" tests are more powerful than non-directional or "two-tailed" tests.
What is a non directional t test?a statistical test of an experimental hypothesis that does not specify the expected direction of an effect or a relationship. Also called nondirectional alternative hypothesis test; nondirectional hypothesis test; two-tailed test.
Is Anova a nondirectional test?From my understanding, the ANOVA is a non-directional test. On a related note, would rewording the hypothesis to "we hypothesized that reaction time may decrease due to the treatment" make it non-directional?
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