The document discusses formulating research questions and hypotheses. It states that the first step is selecting a research topic that can be adequately covered given resource and time constraints. Next, the researcher should take a preliminary literature review to develop solid research questions that will guide the project. Research questions should specify the issue, what is wanted to know, and be answerable and appropriately scoped. Hypotheses predict study outcomes and are tested against descriptive or analytical research questions. The document also discusses null and alternative hypotheses, hypothesis testing methodology, normal distributions, and key concepts like standard error and critical values.

1. Chapter 5: Formulating Research Questions
and Hypotheses

2. Finding a Research Topic
• For your research study, the first thing you have to decide is the topic you plan to investigate. The competence to develop a good research
topic is an important skill. While selecting a topic, it is important to see that the topic you select should be one that can be dealt with in an
appropriately academic manner within the means (resources) and time constraints of your research.
• The first key step for your research process is the development of solid research questions and hypotheses. The first thing you have to do in
this process is to take a preliminary review of the existing literature for your topic. If your research question is written meaningfully and
appropriately, it will guide the implementation of your research project systematically and will provide clear guidelines for the construction of
a logical argument.
• While formulating the research question, you should:
 specify your specific concern or issue
 determine what you want to know about the specific concern or issue
 ensure that the question is answerable
 ensure that your question is not too broad or too narrow

3. Finding a Research Topic (Contd.)
• Research questions are generally of two types:
 Descriptive questions which involve observations to measure quantity. In these questions, there are no
comparison groups/interventions. Purely descriptive questions do not require hypothesis.
 Analytical questions which involve comparisons/interventions to test a hypothesis.
• A hypothesis is one of the key tools in research of advancement of knowledge. It is consistent with existing
knowledge and conducive to further enquiry. It is a prediction about the outcome of a study. Basically, a hypothesis
is a premise. It is an educated guess about a relationship.
• Formulating a hypothesis is an important phase that arrives only after a research question, comprising all the
variables, has been identified without a single flaw by the researcher or a group of researchers.
• When you analyse a data set to determine if two factors might be related, you have to form two hypotheses: null
hypothesis and alternative hypothesis.

4. Finding a Research Topic (Contd.)
• Null hypothesis is usually the one that the researcher wants to gather evidence against or is the hypothesis to be tested. The
alternative hypothesis is usually the hypothesis for which you want to gather supporting evidence by way of observation that could
be obtained from your sampling experiment. The alternative hypothesis is the mathematical opposite of the null hypothesis.
• Hypothesis testing is a very significant topic of statistics. This technique is associated with inferential statistics. The technique is
intensively used by researchers from all sorts of disciplines including psychology, education, marketing and medicine for hypothesis
testing.
• Hypothesis tests belong to the theory of probability, a specialised field of mathematics. Researchers use probability to quantify how
likely it is for an event to occur. Since all inferential statistical methods relate with rare events, which is why probability is used so
extensively. The underlying idea here is that while testing a claim, we must differentiate between two different features of an event:
 An event that easily occurs by chance
 An event that is highly unlikely to occur by chance

5. Normal Distribution
• Normal distributions are widely used statistical tools. They are often referred to as ‘bell curves’, given their bell-type shape,
single-peaked and perfect symmetry. A normal curve represents a distribution of individuals and generally indicates that most
individuals are typical or normal on a particular measurement.
• Following are the features of normal distributions:
 Normal distributions are symmetric around their mean.
 The mean, median and mode of a normal distribution are equal.
 The area under a normal curve is equal to 1.0.
 Normal distributions are denser at the centre and less dense at the tails.
 Normal distributions are defined by two parameters: the mean (μ) and the standard deviation (σ).
 Of the area of a normal distribution, 68.26 per cent, 95.44 per cent and 99.74 per cent are within ±1 standard deviation,
±2 standard deviations and ±3 standard deviations of the mean, respectively.

6. Normal Distribution
• The key concepts in hypothesis testing are:
 the standard error of the mean (σM)
 the central limit theorem (CLT)
 the critical value of Z
 the critical value of t