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Scientific Method, Investigation, Analysis and Evaluation

Null hypotheses, significance and choosing a statistical test

  • 3 things to know
  • A2 1

Overview

Inferential statistics, null and alternative hypotheses, p values and significance, Type I and Type II errors, choosing a t-test, chi-squared or correlation, and worked chi-squared and t-test decisions.

What you need to know

Answer each one before you reveal it.

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Key term

What are inferential statistics?

Key term

What is a null hypothesis?

Key term

What is an alternative hypothesis?

Questions from this subtopic

Each one with the model answer underneath.

  1. 1

    What are inferential statistics?

    Model answer

    Inferential statistics use data from a sample to draw conclusions about a whole population. Statistical tests show whether a difference or relationship is likely to be real or due to chance.

  2. 2

    What is a null hypothesis?

    Model answer

    A null hypothesis states that there is no difference, relationship or association between the variables being tested. A statistical test measures the strength of the evidence against the null hypothesis.

  3. 3

    What is an alternative hypothesis?

    Model answer

    An alternative hypothesis states that there is a real difference, relationship or association between the variables. The alternative hypothesis is accepted only when the null hypothesis is rejected.

  4. 4

    State a suitable null hypothesis for an investigation into whether caffeine changes reaction time.

    Model answer

    Caffeine has no effect on reaction time. Any difference between the caffeine group and the control group is due to chance.

  5. 5

    What does the probability, or p value, from a statistical test mean?

    Model answer

    The p value is the probability of getting results at least this extreme if the null hypothesis were true. A small p value is strong evidence against the null hypothesis.

  6. 6

    What is meant by a statistically significant result?

    Model answer

    A significant result is one that is unlikely to have arisen by chance alone, usually with p below 0.05. The null hypothesis is then rejected.

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