Summary Business statistics - Hospitality Operations Design
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Course
Business statistics
Institution
NHL Stenden Hogeschool (NHL)
For the Business Statistics course of the Hospitality Operations Design module, the notation is the most important. In this document everything you need to know for the exam.
hospitality operations design business statistics nhl stenden hogeschool jaar 2
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NHL Stenden Hogeschool (NHL)
business statistics
Business statistics
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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.
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