Null hypoth, chi-squares, p-values, CI

Mind Map by , created about 6 years ago

HBS108 (Topic 8.4 Statistical inference and hypothesis testing: Conf) Mind Map on Null hypoth, chi-squares, p-values, CI, created by shirley.ha on 09/15/2013.

Created by shirley.ha about 6 years ago
Casuality aka causation & association
Measures of central tendency
Measures of dispersion
The USA, 1919-41
Mapa Mental para Resumir y Conectar Ideas
Marko Salazar
Topic 8.4 Statistical Inference, Statistical Significance and Hypothesis Testing
P-values, Generalisability, Study Limits
P-values e.g
Null hypoth, chi-squares, p-values, CI
1 E.g of null hypothesis
1.1 example of a cohort study looking at the link between smoking and lung cancer
1.2 There is no difference in terms of rates of lung cancer between the group that smoked (the exposed group) and those that did not smoke (the non-exposed group).
1.3 Our cohort study is designed to REFUTE this Null Hypothesis and if we could do this,
1.3.1 it would mean we could accept the Alternative Hypothesis that there IS an actual difference between the exposed group and the non-exposed group Before we could make this claim however, we must apply a test of significance.
1.4 Applying the significance test is a crucial step in hypothesis testing that is the final step in the quantitative research process
2 3 tests of sign aka measures of precision
2.1 chi-squares
2.1.1 statistical test used to determine whether two or more sets of data or populations differ significantly from one another. based on the comparison of observed (sample) data see if that data significantly differs from the population from which it was drawn. use this test for analyzing categorical data.
2.1.2 commonly used statistical technique in medical research, arising when data are categorized into mutually exclusive groups
2.2 p-values
2.3 CI( Confidence Intervals)
2.3.1 concept used for statistical inferences using data from a sample or samples used to create reasonable bounds for the population mean or proportion, based on information from the sample
3 CI
3.1 computed from the sample data
3.2 has a given probability “that the unknown (true) population parameter (e.g., the mean or proportion), is contained within that interval”
3.3 usually reported as 95% CI
3.3.1 which is the range of values within which we can be 95% sure that the true value for the whole population lies.
3.4 However 90% and 99% CI can also be used
3.5 the interpretation of the confidence interval also assists in establishing statistical significance.
3.6 based upon calculated standard errors
3.6.1 give the range of likely values for a population estimate, based on the observed values from a sample
3.7 Standard errors
3.7.1 can represent the "average" deviation between actual and predicted observations
4 looking at standard error of the mean is that
4.1 “provides a statement of probability about the difference between the mean of the sample and the mean of the population”

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