Formulating Hypothesis

Summary

In this lesson on practical research, Ms. K teaches how to formulate a research hypothesis. She explains that a hypothesis is an educated guess or assumption about a population, which can either be proven or disproven through data collection. Ms. K covers two types of hypotheses: the null hypothesis (no statistical significance between variables) and the alternative hypothesis (significant relationship between variables). She also discusses how to craft hypotheses for different research designs, such as correlational, causal-comparative, and experimental studies, emphasizing the role of inferential statistics in making broader inferences from data.

Takeaways

• 😀 A hypothesis is an educated guess or assumption about one or more populations that may or may not be true.
• 😀 Hypotheses are tested through data collection and interpretation, which inform conclusions.
• 😀 There are two main types of statistical hypotheses: null hypothesis (H₀) and alternative hypothesis (H₁).
• 😀 The null hypothesis assumes no statistical significance or relationship between variables.
• 😀 The alternative hypothesis assumes a significant relationship or effect exists between variables.
• 😀 Only studies under inferential statistics use hypotheses, as they make generalizations beyond immediate data.
• 😀 Correlational studies examine the relationship between two variables; null: 'no significant relationship,' alternative: 'significant relationship.'
• 😀 Causal-comparative studies explore cause-and-effect; null: 'no significant difference,' alternative: 'significant difference.'
• 😀 Experimental studies test interventions; null: 'no significant effect/change,' alternative: 'significant effect/change.'
• 😀 Formulating a hypothesis depends on the research design and involves clearly writing null and/or alternative statements.
• 😀 Not all research requires hypotheses; they are specific to studies using inferential statistics.
• 😀 Students can ask questions or seek clarification via their group, Google Classroom, or email.

Q & A

What is a hypothesis in research?

A hypothesis is a claim or statement about the property of one or more populations. It is also known as an educated guess, which researchers use to make assumptions about their study.

What is the difference between null hypothesis and alternative hypothesis?

The null hypothesis (Ho) indicates that there is no statistical significance between the variables. The alternative hypothesis (H1) assumes that there is a statistical significance between the variables.

Can a hypothesis be proven true?

A hypothesis may or may not be true. It is an assumption made by the researcher, and it is tested by collecting and interpreting data.

What is the role of data in hypothesis testing?

Data plays a critical role in hypothesis testing. The decision and conclusion about a hypothesis will always depend on the data that is gathered and interpreted.

What is the null hypothesis example provided in the script?

An example of a null hypothesis is: 'There is no significant relationship between English and Math subject grades of grade 5 pupils.' This assumes there is no statistical significance between the variables.

What does the alternative hypothesis state in contrast to the null hypothesis?

The alternative hypothesis states that there is a significant relationship between the variables. For example, 'There is a significant relationship between English and Math subject grades of grade 5 pupils.'

Under what type of studies are hypotheses applied?

Hypotheses are applied only in studies under inferential statistics. These studies aim to make inferences from the data to broader, more general implications.

What are the different types of research designs where hypotheses are used?

The different types of research designs where hypotheses are used are correlational, causal-comparative, and experimental studies.

How is a hypothesis written under correlational research?

In correlational research, the null hypothesis would state 'There is no significant relationship between the variables,' while the alternative hypothesis would state 'There is a significant relationship between the variables.'

How do hypotheses differ in experimental research?

In experimental research, the null hypothesis would state 'There is no significant effect or change,' while the alternative hypothesis would state 'There is a significant effect or change.'

What is the importance of hypothesis in inferential statistics?

In inferential statistics, hypotheses help to extend the findings beyond the immediate data and make generalizations about broader populations. They guide the process of testing relationships or differences between variables.