Inhoud
Week 1:..................................................................................................................................................2
Levels of measurement and their distributions..................................................................................2
Theoretic distributions:......................................................................................................................5
Central tendency:...............................................................................................................................5
Characteristics of a normal distribution:............................................................................................7
Qualitative vs. quantitative data.........................................................................................................8
Form and correlation (scatterplot)...................................................................................................10
Week 2:................................................................................................................................................15
Cross table, RR, OR etc.....................................................................................................................15
Statistical inference..........................................................................................................................19
Central limit theorem.......................................................................................................................20
Week 3:................................................................................................................................................23
One-sample problem........................................................................................................................23
Hypothesis testing............................................................................................................................23
Type I and type II errors....................................................................................................................25
Different types of problems..............................................................................................................26
Population vs sample vs sampling distribution.................................................................................27
Tukey – Kramer correction...............................................................................................................28
Week 4:................................................................................................................................................29
Mathematical assumptions (different t-tests)..................................................................................29
Chi-square test.................................................................................................................................29
Assumptions linear regression..........................................................................................................30
Residual plot.....................................................................................................................................31
Summarizing figures and tables............................................................................................................32
Notations..........................................................................................................................................32
Formulas test statistics.....................................................................................................................33
Formulas distribution.......................................................................................................................33
Variance and standard deviation......................................................................................................33
Observed and predicted Y................................................................................................................34
Confidence interval simplified..........................................................................................................34
Chi-square test.................................................................................................................................34
Inference on the slope......................................................................................................................35
Confidence interval of the slope.......................................................................................................35
Kiesboom test...................................................................................................................................36
,Week 1:
It is not possible to test a whole population, that is why a sample (subset) is taken from the
population. With this sample, something can be said about the population.
Levels of measurement and their distributions
Nominal Ordinal Interval Ratio
Qualitative/quantitative Qualitative Qualitative Quantitative Quantitative
(categorical) (categorical) (discrete/continuous) (discrete/continuous)
Ordered X X X
Space between scores X X
has a meaning
Ratio of two scores is X
meaningful
Absolute zero X
,Descriptive statistics, one variable
Level of measurement Type of data Graph Statistical techniques
Nominal Qualitative Bar chart Frequencies
Ordinal Qualitative Bar chart + boxplot Frequencies, median
(IQR)
Interval Quantitative (discrete Boxplot + histogram Median, IQR/mean,
and continuous) standard deviation
Ratio Quantitative (discrete Boxplot + histogram Median, IQR/mean,
and continuous) standard deviation
What can be calculated per level of measurement?
Nominal Ordinal Interval Ratio
Mode X X X X
Median X X X
Mean X X
Range X X
Variance/σ X X
Interquartile range X X
Bar chart X X
Boxplot X X
Histogram X X
, Frequency table:
A bar chart is used to summarize the outcome of a qualitative variable. The bars in a bar chart are
not connected and the distance between the bars does not have any meaning:
A histogram is used to summarize the outcome of a quantitative variable. There is no space between
the bars, the width of each bar is meaningful. The surface of each bar in a histogram is exactly equal
to the frequency of the score represented by that bar.
Week 1:..................................................................................................................................................2
Levels of measurement and their distributions..................................................................................2
Theoretic distributions:......................................................................................................................5
Central tendency:...............................................................................................................................5
Characteristics of a normal distribution:............................................................................................7
Qualitative vs. quantitative data.........................................................................................................8
Form and correlation (scatterplot)...................................................................................................10
Week 2:................................................................................................................................................15
Cross table, RR, OR etc.....................................................................................................................15
Statistical inference..........................................................................................................................19
Central limit theorem.......................................................................................................................20
Week 3:................................................................................................................................................23
One-sample problem........................................................................................................................23
Hypothesis testing............................................................................................................................23
Type I and type II errors....................................................................................................................25
Different types of problems..............................................................................................................26
Population vs sample vs sampling distribution.................................................................................27
Tukey – Kramer correction...............................................................................................................28
Week 4:................................................................................................................................................29
Mathematical assumptions (different t-tests)..................................................................................29
Chi-square test.................................................................................................................................29
Assumptions linear regression..........................................................................................................30
Residual plot.....................................................................................................................................31
Summarizing figures and tables............................................................................................................32
Notations..........................................................................................................................................32
Formulas test statistics.....................................................................................................................33
Formulas distribution.......................................................................................................................33
Variance and standard deviation......................................................................................................33
Observed and predicted Y................................................................................................................34
Confidence interval simplified..........................................................................................................34
Chi-square test.................................................................................................................................34
Inference on the slope......................................................................................................................35
Confidence interval of the slope.......................................................................................................35
Kiesboom test...................................................................................................................................36
,Week 1:
It is not possible to test a whole population, that is why a sample (subset) is taken from the
population. With this sample, something can be said about the population.
Levels of measurement and their distributions
Nominal Ordinal Interval Ratio
Qualitative/quantitative Qualitative Qualitative Quantitative Quantitative
(categorical) (categorical) (discrete/continuous) (discrete/continuous)
Ordered X X X
Space between scores X X
has a meaning
Ratio of two scores is X
meaningful
Absolute zero X
,Descriptive statistics, one variable
Level of measurement Type of data Graph Statistical techniques
Nominal Qualitative Bar chart Frequencies
Ordinal Qualitative Bar chart + boxplot Frequencies, median
(IQR)
Interval Quantitative (discrete Boxplot + histogram Median, IQR/mean,
and continuous) standard deviation
Ratio Quantitative (discrete Boxplot + histogram Median, IQR/mean,
and continuous) standard deviation
What can be calculated per level of measurement?
Nominal Ordinal Interval Ratio
Mode X X X X
Median X X X
Mean X X
Range X X
Variance/σ X X
Interquartile range X X
Bar chart X X
Boxplot X X
Histogram X X
, Frequency table:
A bar chart is used to summarize the outcome of a qualitative variable. The bars in a bar chart are
not connected and the distance between the bars does not have any meaning:
A histogram is used to summarize the outcome of a quantitative variable. There is no space between
the bars, the width of each bar is meaningful. The surface of each bar in a histogram is exactly equal
to the frequency of the score represented by that bar.
