Content
Statistics lecture 1..................................................................................................................................1
Standaardafwijking berekenen...........................................................................................................5
Statistics Lecture 2..................................................................................................................................5
Statistics Lecture 3................................................................................................................................12
Statistics College 4 (mostly important pictures from slides).................................................................20
Statistics College 5................................................................................................................................36
Statistics Formulas................................................................................................................................57
Mean of population..........................................................................................................................57
Mean of sample................................................................................................................................57
Z-Score..............................................................................................................................................57
Z-score for sample mean..................................................................................................................58
Standard deviation...........................................................................................................................58
Variance............................................................................................................................................59
Standard error..................................................................................................................................60
ANOVA..............................................................................................................................................60
Statistics lecture 1
Definitions
- Variable
o A variable is a characteristic or condition that changes or has different values for
different individuals
- Data
o Data are measurements or observations
- Dataset
o A dataset is a collection of measurements or observations
- Datum
o A datum is a single measurement or observation and is commonly called a score or
raw score
- Discrete variable
o A discrete variable consists of separate, indivisible categories. No values can exist
between two neighboring categories
- Continuous variable
o For a continuous variable, there are an infinite number of possible values that fall
between any two observed values. A continuous variable is divisible into an infinity
number of fractional parts
Population vs. sample
, - Research question: do male UU students sleep more than female UU students?
- Population of interest: all male and female UU students
- Sample 1: group of male and female students in this course
o Population to which results can be generalized: students in this course, if they are
randomly sampled
- Sample 2: group of UU male and female students
o Population to which results can be generalized: UU students, if they are randomly
sampled
Descriptive vs. Inferential statistics
- Organize and simplify (descriptive statistics)
- Interpret the results (inferential statistics)
o There is a difference
o There is no difference
Definitions
- Descriptive statistics: descriptive statistics are statistical procedures used to summarize,
organize and simplify data
- Inferential statistics: inferential statistics consist of techniques that allow us to study samples
and then make generalizations about the population from which they were selected
- Sampling error: sampling error is the naturally occurring discrepancy, or error, that exists
between a sample statistic and the corresponding population parameter
Variable measurement scales
- Nominal
- Ordinal
- Interval
- Ratio
Nominal
- A set of categories with different names
- Gender, Majors, etc.
Ordinal
- A set of categories with different names organized in ordered sequence
, - Does not specify how much larger/smaller
Interval
- Ordered categories with in between intervals of the same size
- Like CM’s on a ruler, or temperature
- Does specify how much larger/smaller
- No natural zero value, zero does not mean absence of something
Ratio
- Interval scale with absolute zero point
- Zero value means absence of something
- Like weight
, Measures of Variability
- Range
o Difference between largest and smallest score of distribution
- Variance
o Average of the squared distances (deviations) from the mean
- Standard deviation
o Square root of the variance
o A measure of the standard distance from the mean
Degree of freedom
- Population
o Mean if known
o Deviations are computed from a known mean
- Sample variance as estimate of population
o Population mean is unknown
o Using sample mean restricts variability
- Degrees of freedom
o Number of scores in sample that are independent and free to vary
o Degrees of freedom df = n – 1
Statistics lecture 1..................................................................................................................................1
Standaardafwijking berekenen...........................................................................................................5
Statistics Lecture 2..................................................................................................................................5
Statistics Lecture 3................................................................................................................................12
Statistics College 4 (mostly important pictures from slides).................................................................20
Statistics College 5................................................................................................................................36
Statistics Formulas................................................................................................................................57
Mean of population..........................................................................................................................57
Mean of sample................................................................................................................................57
Z-Score..............................................................................................................................................57
Z-score for sample mean..................................................................................................................58
Standard deviation...........................................................................................................................58
Variance............................................................................................................................................59
Standard error..................................................................................................................................60
ANOVA..............................................................................................................................................60
Statistics lecture 1
Definitions
- Variable
o A variable is a characteristic or condition that changes or has different values for
different individuals
- Data
o Data are measurements or observations
- Dataset
o A dataset is a collection of measurements or observations
- Datum
o A datum is a single measurement or observation and is commonly called a score or
raw score
- Discrete variable
o A discrete variable consists of separate, indivisible categories. No values can exist
between two neighboring categories
- Continuous variable
o For a continuous variable, there are an infinite number of possible values that fall
between any two observed values. A continuous variable is divisible into an infinity
number of fractional parts
Population vs. sample
, - Research question: do male UU students sleep more than female UU students?
- Population of interest: all male and female UU students
- Sample 1: group of male and female students in this course
o Population to which results can be generalized: students in this course, if they are
randomly sampled
- Sample 2: group of UU male and female students
o Population to which results can be generalized: UU students, if they are randomly
sampled
Descriptive vs. Inferential statistics
- Organize and simplify (descriptive statistics)
- Interpret the results (inferential statistics)
o There is a difference
o There is no difference
Definitions
- Descriptive statistics: descriptive statistics are statistical procedures used to summarize,
organize and simplify data
- Inferential statistics: inferential statistics consist of techniques that allow us to study samples
and then make generalizations about the population from which they were selected
- Sampling error: sampling error is the naturally occurring discrepancy, or error, that exists
between a sample statistic and the corresponding population parameter
Variable measurement scales
- Nominal
- Ordinal
- Interval
- Ratio
Nominal
- A set of categories with different names
- Gender, Majors, etc.
Ordinal
- A set of categories with different names organized in ordered sequence
, - Does not specify how much larger/smaller
Interval
- Ordered categories with in between intervals of the same size
- Like CM’s on a ruler, or temperature
- Does specify how much larger/smaller
- No natural zero value, zero does not mean absence of something
Ratio
- Interval scale with absolute zero point
- Zero value means absence of something
- Like weight
, Measures of Variability
- Range
o Difference between largest and smallest score of distribution
- Variance
o Average of the squared distances (deviations) from the mean
- Standard deviation
o Square root of the variance
o A measure of the standard distance from the mean
Degree of freedom
- Population
o Mean if known
o Deviations are computed from a known mean
- Sample variance as estimate of population
o Population mean is unknown
o Using sample mean restricts variability
- Degrees of freedom
o Number of scores in sample that are independent and free to vary
o Degrees of freedom df = n – 1
