PSYC105 Lecture Notes - Lecture 5: Central Limit Theorem, Null Hypothesis, Statistical Inference
21 May 2018
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PSYC105 STATISTICS
Week Five: Fundamental Concepts
Lecture Overview
- Normal Distribution
o Empirical rule
o Standardised scores (z scores)
o Sampling distribution of sample means and the central limit theorem
- Formal hypothesis testing
o Statistical inference and errors
- Types of numbers
o Statistical significance vs effect size
o Confidence intervals
- Types of statistical tests
Probability
- Probability: how likely something is to occur
- Range from 0 to 1 (0% to 100%)
Normal Distribution
- Called oral eause it is typial, oo, oral
Empirical Rule
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Document Summary
Normal distribution: empirical rule, standardised scores (z scores, sampling distribution of sample means and the central limit theorem. Formal hypothesis testing: statistical inference and errors. Types of numbers: statistical significance vs effect size, confidence intervals. Probability: how likely something is to occur. Range from 0 to 1 (0% to 100%) Called (cid:374)or(cid:373)al (cid:271)e(cid:272)ause it is typi(cid:272)al, (cid:272)o(cid:373)(cid:373)o(cid:374), (cid:858)(cid:374)or(cid:373)al(cid:859) Z-scores are standardised scores, measuring the difference between a score and the mean, expressed in standard deviation units. Z-scores are useful if we want to compare scores on difference scales. Z = (score mean) / standard deviation. Distribution of sample means will be approximately normal. Mean of the sample means will be the same as the population mean. Standard deviation of sample means = standard error. Analysing data from a sample, to see whether it can make a contribution to a field of knowledge.
