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Normal Distribution Psychology

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Normal Distribution Psychology

We use distributions to create graphical illustrations of the frequency of different scores in a data set. Normal distributions are bell-shaped and symmetrical. The mean, median and mode values are the centre of the bell, with few extreme scores. Many individual characteristics are normally distributed in the population, meaning most individuals will score around the average, with few people being much above or below the mean.

The most popular normal distribution in psychology is the population's distribution of intelligence (IQ). People's scores on IQ tests tend to be normally distributed. Most people score around average, with rare cases of people scoring very high or very low on IQ tests. Similarly, height, shoe size or personality traits like extraversion or neuroticism tend to be normally distributed in a population.

Normal Distribution Psychology, Bell curve, StudySmarterNormal distribution of data, flaticon.com

Definition of normal distribution in psychology:

We can define normal distributions in psychology as:

Normal distributions are bell-shaped, symmetrical graphical illustrations where values such as the mean, median and mode sit at the centre of the bell, and extreme scores tail off at either end.

Features of normal distributions in psychology

Normal distributions have three main features:

  1. They are symmetrical, meaning that the distribution of scores larger than the mean should be symmetrical to the distribution of scores smaller than the mean. An equal amount of extreme scores should fall on both sides of the mean.
  2. Normally distributed data forms a bell curve. The mean, median and mode values tend to be similar or the same and create the centre (the peak) of the distribution.
  3. The tails of the distribution meet the x-axis at infinity, meaning they shouldn't touch the x-axis (asymptotic).

Normal distribution bell curve in psychology

The normal distribution can be illustrated with a bell curve, which suggests that most of our data is clustered around the mean value in the distribution's centre. The probability of values being close to the mean is much higher than the values being far from the mean because the frequency of scores at the distribution's tails is much lower than in the centre.

The mean, median, and mode in a normal distribution

When the data is normally distributed, mean, median, and mode tend to be the same or very similar. Let's recap what each of these values indicates and how to calculate them.

  • The mean is the average value of our data. To calculate the mean, add all the values collected and divide their sum by the number of data points (e.g. the number of participants or measurements).
  • The median is the middle value in your data set. Order your data from the lowest to the highest value to find the median. If your number of data points is odd (e.g. 7), choose the value in the middle (the fourth value); if it's even (e.g. 8), then your median is the average of the two middle values (the average of the fourth and the fifth value).
  • The mode is the most frequently repeating value in your data set. To find the mode, order your data from the lowest to the highest; the number appearing most frequently is your mode. If none of your values repeats, your data set has no mode.

You asked five students about how many hours (h) they slept last night. You collected the following data: 9h, 4h, 6h, 6h, 5h. The mean of your data is 6, the median is the middle value when the data is ordered from lowest to highest, which in our case is also 6, and the mode, which is the most frequent value, is also 6.

Normal Distribution Psychology, Bell, StudySmarterNormal distributions take the shape of a bell curve, flaticon.com

Normal and skewed distributions in psychology

One of the main features of the normal distribution is symmetry and characteristic bell shape. What happens if our mean, median and mode are different and the distribution isn't symmetrical? In this case, we can identify negatively or positively skewed distribution.

Skewed distribution

Skewed distributions are not symmetrical; they have their peak off centre and extended tail in one direction. In the case of skewed distributions, the mean is no longer in the centre. It is shifted due to a large number of extreme scores to one side of the distribution. Such distributions no longer form a bell curve.

Positively skewed distributions have their peak shifted to the left with a longer tail to the right.

Negatively skewed distributions have their peak shifted to the right with a longer tail to the left.

Examples of normal and skewed distributions

If we know that our mean, median and mode are the same or similar, we can estimate that the data is normally distributed around these values.

MeanMedianMode
1616.516

Normal Distributions Psychology, normal distributions, StudySmarterNormal distribution, StudySmarter Originals, Alicja Blaszkiewicz

If there is a bigger difference between the mean, median and mode, the distribution won't be normal. Here, the mode and median are higher than the mean, suggesting negatively skewed our data.

MeanMedian Mode
14.51618

Normal Distribution Psychology, normal distributions, StudySmarter

Negatively skewed distribution, StudySmarter Originals, Alicja Blaszkiewicz

In this case, our measures of central tendency are quite different; the mode and the median are lower than the mean, suggesting a positively skewed distribution.

MeanMedianMode
1815.514

Normal Distribution Psychology normal distributions StudySmarter

Normal distribution in psychological testing

Normal distribution are quite important in psychological research, especially when making predictions. Here are some examples of normal distributions in psychological testing.

Clinical practice

The normal distribution is often used in psychological testing when interpreting test scores. As many psychological traits or symptoms are normally distributed across the population, by looking at where an individual score falls on the distribution, we can get an idea of how much it deviates from the average, which can aid diagnosis or help identify people at risk.

Research

Normal distributions are also crucial for research and statistical testing. Inferential statistical tests (e.g. the t-test) that we use to decide whether to reject our null hypothesis mostly require the data to be normally distributed. If our data is not normally distributed, we will need to use less sensitive, nonparametric statistical tests.


Normal Distribution Psychology - Key takeaways

  • We use distributions to create graphical illustrations of how the frequency of data is distributed.
  • Normal distributions are bell-shaped and symmetrical. The mean, median and mode values are the centre of the bell curve, with few extreme scores. Tails of the normal distribution meet the x-axis at infinity, meaning they should be above the x-axis when graphically represented (asymptotic).
  • Mean is the average value, the median is the middle value, and mode is the most frequent value in a data set. We can estimate the data distribution based on the mean, median and mode values.
  • Skewed distributions are not symmetrical; they have their peak off centre and have an extended tail in one direction.
  • Normal distributions can be helpful for clinical diagnosis. In research, normally distributed data is also necessary to test the statistical significance of our results using parametric statistical tests like the t-test.

Frequently Asked Questions about Normal Distribution Psychology

Normal distribution tells us about the frequency of scores. Most scores will cluster in the middle around the distribution centre, and extreme scores that are further away from the mean will be less frequent and symmetrically distributed.

Parametric statistical tests require the data to be normally distributed. We can choose an appropriate statistical test based on whether our data is normally distributed or not. So, normal distributions are important in research in psychology.

A normal distribution curve is achieved when the mean, median and mode values are similar and at the distribution centre. The normal distribution also requires symmetry and very few extreme values.

The normal distribution is bell-shaped; the mean, median and mode values are similar and at the distribution centre. The normal distribution is symmetrical and has few extreme values. The tail ends of the normal distribution are asymptotic.

We use distributions to create graphical illustrations of how the frequency of data is distributed. Normal distributions are bell-shaped and symmetrical. The mean, median and mode values are the centre of the bell, with few extreme scores.

Final Normal Distribution Psychology Quiz

Question

What do distributions represent?

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Answer

Distributions represent how the frequency of scores is distributed.  

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Question

What is a normal distribution?

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Answer

Normal distributions are bell-shaped and symmetrical. The mean, median and mode values are the centre of the bell, with few extreme scores.  

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Question

What individual characteristics are normally distributed in the population?

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Answer

For example, IQ, personality traits, shoe size, height, and weight.

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Question

What are the 3 main features of normal distributions?

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Answer

1. They are symmetrical, meaning that the distribution of scores larger than the mean should be symmetrical to the distribution of scores smaller than the mean.

2. Normal distribution is because it is bell-shaped. The mean, median and mode values tend to be similar or the same and create the centre of the distribution. 

3. The tails of the distribution meet the x-axis at infinity.

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Question

How are the scores distributed in normally distributed data? 

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Answer

  • Most of the data is clustered around the mean value that is in the centre of the distribution. 
  • The frequency of scores at the tails of the distribution is much lower than in the centre. 
  • Scores are distributed symmetrically around the mean.

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Question

Let's say that anxiety is a normally distributed trait in the population. What's the probability of having average levels of anxiety compared to extreme levels of anxiety?

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Answer

The probability of scoring around the average is larger than getting extreme scores in the case of normally distributed traits. This is because normal distribution suggests that anxiety levels for most people in the population will be clustered around the mean.

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Question

Which value measures the average score?

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Answer

mean

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Question

Which value reflects the middle score?

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Answer

median

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Question

Which value reflects the most frequent score?

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Answer

mode

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Question

Is the following statement true or false?

When the data is normally distributed mean, median and mode tend to be the same or very similar. 

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Answer

True

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Question

Which distributions are symmetrical?

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Answer

Normal distributions

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Question

Describe the characteristics of skewed distributions.

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Answer

Skewed distributions are not symmetrical, they have their peak off centre and have an extended tail in one direction. The mean is no longer in the centre it is shifted due to a large number of extreme scores, to one side of the distribution. Such distributions no longer form a bell curve. 

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Question

What are positively skewed distributions?

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Answer

Positively skewed distributions have their peak shifted to the left with a longer tail to the right.

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Question

What are negatively skewed distributions?

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Answer

Negatively skewed distributions have their peak shifted to the right with a longer tail to the left.

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Question

What are the applications of normal distributions in psychology?

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Answer

Normal distributions can be helpful for clinical diagnosis


In research normally distributed data is also necessary to test the statistical significance of our results using parametric statistical tests like the t-test.

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