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M&T > Task 2 > Flashcards

Task 2 Flashcards

1
Q

Which 2 main types of data are there?

A

Categorical data

Quantitative data

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2
Q

Which 2 categories of categorical data do you know?

A

Nominal (naming)

Ordinal (ordering)

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3
Q

Which type of categories does nominal data have?

Name an example

A 
Equal categories (without order) 
gender: male/female
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4
Q

Which type of categories does ordinal data have?

Name an example

A 
ordern categories (with order) 
education level (low/ middle / high)
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5
Q

By using categorical data, are the distances on scale meaningful?

A

no

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6
Q

Which suitable table do you use for categorical data?

A

frequency table

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7
Q

Which suitable graphs do you use for nominal data?
What are classical representations?
Name 2

A

Pie chart

Bar chart

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8
Q

Which suitable measure of central tendency do you use for nominal data?

A

mode

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9
Q

Which suitable measures of central tendency do you use for ordinal data?

A

Mode

Median

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10
Q

Which suitable measure of central tendency do you use for quantitative data (interval & ratio) ?

A

Mode
Median
Mean

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11
Q

Is there a suitable measure of dispersion for categorical data?

A

no

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12
Q

Which suitable measures of dispersion (Verteilung) do you use for quantitative data?

A 
Interquartile range (IQR)
Standard deviation
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13
Q

Name 2 main data scores which are used by quantitative data

A

Interval (distance)

Ratio (rate)

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14
Q

Which suitable table do you use for quantitative data?

A

Stem and leaf plot

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15
Q

Which suitable graph do you use for quantitative data?

Name 2 classical representations

A

Histogram

boxplot

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16
Q

What do you know about the distance between the variables by using interval? Example

A

Meaningful numbers, for instance IQ (50-150)

The distance between consecutive units is always equally large

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17
Q

What do you know about ratio

A

an interval variable with an absolutions zero point, for instance age

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18
Q

When do you use a stem and leaf plot?

A

if you have a low number of recordings

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19
Q

What are the advantages of a histogram?

A

easy to represent many data points

easy to interpret data roughly (ungefähr)

20
Q

Which are the 3 special interest points of a histogram?

A 
Extreme values (outliers) 
Number of peaks (modes) 
Symmetry
21
Q

When do you use the box-plot?

A

visual representation of large data set
fast recognition of outliers
easy comparison of several groups

22
Q

Name 4 Middle values / suitable measures of central tendency

A

mean
median
mode
IQR

23
Q

Mean

Definition?
Calculation?
How to deal with Outliers?
Example

A

• Average value / the scores center of mass
• Calculation: adding all values, dividing sum by total numbers of observations
• Sensitive to outliers
(be careful using it in case of skewed distributions or outliers)

Example:
1-3-3-4-9
Sum=20
Mean= 20/5= 4

24
Q

Usage of mean

A

for quantitive data (interval variables and up)

tells you something about the frequency, order and value of scores

25
Q

Median

Definition?
Determing?
How to deal with outliers?
Example

A
  • Middle value (50% lies below and 50% above)
  • Determining: ordering all values from small to large and picking the middle (N+1):2
  • Robust towards outliers

Example:
1-2-4-4-5
• Median: 4

26
Q

Usage of median

A

okay for ordinal variables and up (interval and ratio)

tells you some thing about the frequency and order of scores

27
Q

Mode

Definition?
Determing?
How to deal with outliers?
Example

A
  • Highest frequency of value
  • Determining: which value or category appears most frequent / often
  • Robust towards outliers

Example:
1-2-2-4-12
• Mode: 2

28
Q

usage of mode

A

is always okay

tells you something about the frequency of scores

29
Q

deutsches Wort für distribution

A

Verteilung

30
Q

deutsches Wort für skewed

A

verzerrt

31
Q

What is a Z-score?

A
  • A standardized measure of standard deviations.
  • Example: if SD=15 and a person has a score 15 points above the mean his Z-score= +1
  • Measures how many standard deviations an observed value differs from the mean
  • Does not change shape of distribution
  • Measure of center and spread might change
32
Q

What is the Standard deviation

A

the average deviation from the mean

the squared value of this is called the variance

33
Q

How do you calculate the standard deviation?

A

take the difference of each score from the mean, square these difference, sum them up, divide them by the total amount of scores minus 1 and take the square rout of the outcome

34
Q

Usage of standard deviation

A

okay for quantitative data (interval variables)

is not resistant to outliers

35
Q

Interquartile range IQR

A

the range between which the 50% middle scores fall

IQR= Q3-Q1

for interval variables

36
Q

Five-number-summary

A

five quantities in a row which summaries the complete distribution
minimum-Q1(25%)-median-Q3(75%)-maximum

37
Q

1,5* IQR criterion

A

to identify a score as an outlier

downward outlier:
Q1-(1,5IQR)
is the score even lower than this outcome, we consider it as an outlier
upward outlier:
Q3+(1,5IQR)
if a score is even higher than this outcome, we say its an outlier indeed

38
Q

centring

A

shift all scores such that the mean becomes 0
C=X-mean
the shape of the distribution gets not effected at all; the only thing that changes is the mean

39
Q

Standardising

A

shift all the scores such that the mean becomes 0, and then change the scores such that the standard deviation becomes 1 as well
(Z-formula)

40
Q

Multiplying

A

multiply all scores by a certain number

X´= a*X

41
Q

What is the difference between a histogram and a bar graph?

A

A bar graph presents different groups (categorical data), a bar graph has space between its bars

42
Q

Can the variance be negative? Explain

A

no it can’t because its the standard deviation im Quadra

43
Q

if you have a normal distribution how much percent does Z1 include?

A

68%

44
Q

If you have a normal distribution how much percent does Z2 include

A

95%

45
Q

If you have a normal distribution how much does Z3 include?

A

99%

M&T (8 decks)

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