Aims and Hypotheses

Difference Between Aims and Hypotheses: Psychology

When you write a research report, you should state the aim first and then the hypothesis.

The aim is a broad starting point that gets narrowed down into the hypothesis.

Types of Hypotheses

Before we get into the types of hypotheses, let's quickly recap the hypotheses' components.

There are two types of hypotheses: null and alternative hypotheses.

A null hypothesis states that the independent variable does not influence the dependent variable. The null hypothesis states that changes/ manipulating the IV will not affect the DV.

An alternative hypothesis states that the independent variable has an effect on the dependent variable. Often, it is the same (or very similar) to your research hypothesis.

Fig. 1. Would you score well on exams when you did not sleep long enough? Pixabay.com.

The alternative hypothesis can be further sub-categorised into a one- or two-tailed hypothesis. A one-tailed hypothesis (also known as a directional hypothesis) suggests that the results can go one way, e.g. it may increase or decrease. And a two-tailed (also known as a non-directional hypothesis) is exactly the opposite; there are two ways the results could expectedly go.

Aims and Hypothesis in Research

In research, aims and hypotheses play major roles. They are the part of the research that sets you up for the rest of the study. Without strong research aims and hypotheses, your research will lack direction.

First, let's go over the function of research aims.

Research aims provide an overview of the research objective; this allows all researchers to be on the same page about the purpose of the research. Aims also describe why the research is needed and how it complements existing research in the field.

Duplicating research can sometimes be useful, but most times, researchers want to conduct their own new research.

Outside of the researchers, readers can then identify the research topic and whether it interests them.

But what information do hypotheses provide?

Hypotheses identify the variables studied in an experiment. They describe expected results in terms of the effect of the independent variable on the dependent variable. When readers see the hypothesis, they should know exactly what the researcher expected in the study's outcome (remember, sometimes the researcher can be wrong).

Typically, researchers use hypotheses for statistical tests such as hypothesis testing, which allows them to determine if the original predictions are correct. Hypotheses are helpful because the reader can quickly identify the variables, the expected results based on previous research, and how the experiment should measure these variables.

Psychological research must meet a standard for the psychological research community to accept it.

Components of Hypotheses

When writing research hypotheses, there are several essential things to consider, including:

• The hypotheses must be clear and concise;

  • it must be easy to understand and not contain irrelevant details.

• The researcher must predict what they expect to find based on reading previous research findings.

• The researcher must explain how they arrived at their predictions, citing evidence from prior research.

• The researcher must identify all variables they will study.

Additionally, the research must operationalise the hypotheses and describe how the variables will be measured.

Example Hypothesis

A hypothesis denotes a relationship between two variables, the independent and dependent variables. An example hypothesis is the more you sleep, the less tired you will feel.

Aims and Hypotheses: Psychology

Now that we understand the difference between aims and hypotheses, let's take a closer look at their function.

In psychology, aims and hypotheses function very similarly to other research fields. They set up the purpose of a study so that the researchers and readers understand its goals.

The aims establish the reasoning behind the study and why that specific topic is being researched. And the hypotheses share the researchers' expectations. It outlines what the researchers expect when the IV is manipulated.

Aims and Hypotheses in Research Example

As we have learned, aims and hypotheses are crucial in setting up successful research. They exist within every study and help outline the goals and outcomes the researchers expect. To further understand the aims and hypotheses in psychological research, let's look at a famous study – Asch's line experiment.

Solomon Asch conducted a study in 1951 about conformity. This study has become renowned for exposing the strong effects of conformity in a group setting. Asch put one participant in a room with seven strangers, people he said were other participants but were, in fact, confederates.

The participants were tasked with trying to match one line to three other lines. Initially, the confederates would answer correctly, but as the trials continued, they all answered incorrectly. Would the participant still give the correct answer, or would they be swayed by conformity and be wrong?

Asch found that 74% of participants conformed at least once, even though they were obviously giving the wrong answer.

Fig. 2. Would you be influenced to conform during a lecture? Pixabay.com.

In this experiment, the aim was to look at the effects of conformity. More specifically, Asch aimed to see how impactful groups' pressures are on an individual's conformity. Asch hypothesised that participants would conform to the group when the confederates answered incorrectly due to social pressure.

Since we know the study's outcome, we know that Asch stayed true to his aims and provided supporting evidence for his hypothesis.

Explicit Research Aims, Objectives, and Hypotheses

An explicit research necessity across all disciplines is the operalisation of variables. When talking about operationalising a variable or hypothesis, it means that the term is defined so clearly and succinctly that there is no confusion or any grey area concerning what it means.

When operationally defining variables, researchers need to not only define what the variable is but also how they will measure it. Operationally defined hypotheses not only include detailed descriptions of variables and the outcome but also the relationship between the variables.

While operationally defining variables and hypotheses might seem like a simple task, it is extremely important for a successful outcome.