Introduction to quantitative statistics Flashcards
What is a research hypothesis?
Working assumption or prediction about the expected outcome of a study
Which statistics inform on the hypothesis testing?
Inferential statistics
- is there enough empirical support?
What is the meaning of the null hypothesis (H_0)?
Any differences or relationships between variables are due to random or chance
What is the meaning of the experimental (alternative) hypothesis (H_1)?
The independent variable does have an effect on the dependent variable
Can we treat the experimental (alternative) hypothesis as true or proven?
No
We can only prove that something is not true.
-> demonstrate that null hypothesis is not true = IV has an effect on DV
What is the purpose of descriptive statistics?
Summarise aspects of the results (collected data)
What is the purpose of inferential statistics?
- Inform of significant patterns or relationships in the data
- Generalise results from sample to general population
When is the null hypothesis (H_0) rejected?
When the observed difference between experimental groups (conditions) is significantly large
Which statistical tests explore relationships or differences between two variables?
Bivariate statistical tests
Which statistical tests explore relationships or differences between a number of variables?
Multivariate statistical tests
What is the purpose of a test statistic?
Summarizes the relationship between variables or groups
Which statistical index informs on the correlation between values?
Pearson’s r
Which statistical index informs on the statistical significance of a relationship between variables?
p-value
What is the meaning of the p-value?
Probability of finding the test statistic if there was no difference between variables or groups
-> How probable is it that a random error alone could produce the changes in the DV?
Unlikely (p < .05): it’s the IV having an effect on the dependent variable
How is the probability that the independent variable is having an effect on the dependent variable calculated?
Indirectly calculated by discounting the likelihood of the effect being produced by random error
= p-value
What does empirical probability refer to?
Calculation of probability when the outcomes are not equally likely to occur
How is empirical probability calculated?
[number of favourable outcomes] / [total number of trials]
When does the empirical probability of an event increase?
As the observed sample (number of trials) increases
e. g. 9 successes out of 100 trials
- > increasing the number of trials increase the likelihood of favourable outcomes
With a 95% confidence interval, when can the null hypothesis be rejected at the 5% level?
If the null value (0) is not contained in the 95% CI
With a 95% confidence interval, when can the null hypothesis be accepted at the 5% level?
If the 95% CI contains the null value (0)
What is a ‘Type I error’?
‘false positive’
Falsely rejecting the null hypothesis
What is a ‘Type II error’?
‘false negative’
Accepting our null hypothesis in error
What is the power of a hypothesis?
The probability of not committing a Type II error
Which factors determine the power of a test?
- Sample size
- Effect size
- Variability
- Alpha level (α)
- Type of test
What is the meaning of the alpha level (α) of a test?
Likelihood of detecting a difference
- increasing the alpha level increases the risk of Type I error
How do you estimate the sample size needed to have a good chance to detect a defined effect size?
Do a power analysis
