Samenvatting document Business statistics
Variables
A nominal variable:(categorical)
> Categories
- Marital status, Male or female, eye colour.
An ordinal variable: (categorical)
> Categories + Ranking order
- 2, 3 and 4- star restaurant, Finishing position in a race, Olimpic medals
An interval variable: (Numerical)
> Rank order + Equal distance
- Intelligence, Temperature
A ratio variable starts:(Numerical)
> Rank order + Equal distance + zero
- Reaction time, Weight, Age, euro’s.
Mode
o The mode is the score that occurs most frequently
o Nominal, Ordinal, Interval, Ratio
Median
o Order the scores from the lowest to the highest score and then simply find the
middle score
o Ordinal, Ratio, Interval
Mean
o The average score
o Interval, Ratio
Standard Deviation
o The average deviation from the mean
o Interval, Ratio
T-test
o Used to compare means from two separate samples
o Interval, Ratio
Chi-square
o Used to compare proportions of cases in categories of a single nominal variable
with proportions expected under the null hypothesis
o Nominal, Ordinal
Correlation
, o Which describes the degree of a linear relationship between two interval/ratio
variables denoted by R
o Interval, Ratio
Regression
o Predict the most often occurring category in a cross table
o Interval, Ratio
Lecture 1: standard score
Lager dan 105?
Z = (x - µ) / Ơ
Z = (105-100)/10 = 0.50
P = ( Z< 0,5) .6915 (69.15%)
Hoger dan 105?
Z = (x - µ) / Ơ
Z = (105-100)/10 = 0.50
P= (Z > 0,5) .3085 (30.85%)
Hoe groot is de kans dat iemand betaald tussen 100 en 105?
Z = (x - µ) / Ơ
Z = (105-100)/10 = 0.50
P= ( 0< Z 0,< 5) .1915 (19.15%)
Lecture 2: Hypothesis testing.
Population = everyone we are interested in
Sample = the people we actually research
Step 1 › Formulate the hypothesis to test.
Step 2 › Find the statistical value to use.
Step 3 › Compute the sampling distribution for the hypothesis.
Step 4 › Check if the sample data matches this sampling distribution.
Lecture 3: Group differences.
Variables
A nominal variable:(categorical)
> Categories
- Marital status, Male or female, eye colour.
An ordinal variable: (categorical)
> Categories + Ranking order
- 2, 3 and 4- star restaurant, Finishing position in a race, Olimpic medals
An interval variable: (Numerical)
> Rank order + Equal distance
- Intelligence, Temperature
A ratio variable starts:(Numerical)
> Rank order + Equal distance + zero
- Reaction time, Weight, Age, euro’s.
Mode
o The mode is the score that occurs most frequently
o Nominal, Ordinal, Interval, Ratio
Median
o Order the scores from the lowest to the highest score and then simply find the
middle score
o Ordinal, Ratio, Interval
Mean
o The average score
o Interval, Ratio
Standard Deviation
o The average deviation from the mean
o Interval, Ratio
T-test
o Used to compare means from two separate samples
o Interval, Ratio
Chi-square
o Used to compare proportions of cases in categories of a single nominal variable
with proportions expected under the null hypothesis
o Nominal, Ordinal
Correlation
, o Which describes the degree of a linear relationship between two interval/ratio
variables denoted by R
o Interval, Ratio
Regression
o Predict the most often occurring category in a cross table
o Interval, Ratio
Lecture 1: standard score
Lager dan 105?
Z = (x - µ) / Ơ
Z = (105-100)/10 = 0.50
P = ( Z< 0,5) .6915 (69.15%)
Hoger dan 105?
Z = (x - µ) / Ơ
Z = (105-100)/10 = 0.50
P= (Z > 0,5) .3085 (30.85%)
Hoe groot is de kans dat iemand betaald tussen 100 en 105?
Z = (x - µ) / Ơ
Z = (105-100)/10 = 0.50
P= ( 0< Z 0,< 5) .1915 (19.15%)
Lecture 2: Hypothesis testing.
Population = everyone we are interested in
Sample = the people we actually research
Step 1 › Formulate the hypothesis to test.
Step 2 › Find the statistical value to use.
Step 3 › Compute the sampling distribution for the hypothesis.
Step 4 › Check if the sample data matches this sampling distribution.
Lecture 3: Group differences.
