Presentation / Display of data

Question 1

What is another word for Nominal data?

Answer 1

Categorical

Question 2

What is Nominal (Categorical) data?

Answer 2

categories into which observations fall, without any quantitative element, e. g. Eye colour, ABO blood group.

Question 3

What is binary data?

Answer 3

Data where there are just TWO categories, e. g. Sex, HIV status.

Question 4

What is Ordinal data?

Answer 4

Ordinal data have a quantitative element in the categories, but no well defined scale of measurement, e. g. The Apgar scale of condition of the new-born (from 0 to 10), Stages of cancer (I, II, III, IV).

Question 5

what is Discrete numerical data?

Answer 5

Discrete numerical data have a well-defined numerical scale of measurement confined to whole numbers: Number of living children a woman has, Number of times a patient has been admitted to hospital.

Question 6

What is Continuous numerical data ?

Answer 6

That is data where the observations may vary over some continuous numerical range: Age, Height, Body temperature, Blood pressure.

Question 7

What is Frequencies?

Answer 7

How often each value occures.

Question 8

How do you express Relative frequencies?

Answer 8

Percent

Question 9

Which two ways are the most popular forms to display frequency?

Answer 9

Bar chart and pie chart.

Question 10

How does the Pie chart work?

Answer 10

For the Pie chart the frequency is represented by the area i. e. the propotion of each ‘slice’ equals the relative frequency.

Question 11

How does the bar chart work?

Answer 11

The hight of each bar represents the corresponding frequency.

Question 12

Which two ways are the most popular forms to display numerical data?

Answer 12

Dotplots and histograms

Question 13

How does a dotplot work?

Answer 13

Dotplot represents numeric data as dots lying on the real line with repeating entries stack upon each other

Question 14

How does a Histogram work?

Answer 14

Histogram is a vertical bar chart. The range of data is split into disjoint regions: bins, and bars are drawn on their bases so that the areas of the bars (not heights!, in general) represent frequencies of data in each region.

Question 15

What is the midpoint of classes/bins called?

Answer 15

class marks

Question 16

How many bins should you choose?

Answer 16

between 6-12

Question 17

What is the difference between unimodal, bimodal and multi-modal?

Answer 17

distribution has one, two or more distinctive peaks.

Question 18

Explain what skew is

Answer 18

one tail is longer/heavier than another

Question 19

What is Shape of distribution?

Answer 19

Shapes for comparison

Question 20

What are outliers?

Answer 20

are there observations which appear to be different from the rest of the data. We might want to exclude them from the analysis.

Question 21

What is the location?

Answer 21

How is the values of the data distributed?

Question 22

If a curve is skew to the right, what does it look like?

Answer 22

The “top” is located to the left and the “tail” to the right

Question 23

What is the mean value?

Answer 23

Average

Question 24

What is the median value?

Answer 24

The middle value,
If N is odd, median = middle value.
If N is even, median = Average of two middle values.

Question 25

How does the median and mean react to outliers?

Answer 25

The mean is sensitive to outliers, i. e. its value is greatly affected by their presence; whereas the median is robust against effects of extreme values. Hence median is more reliable measure of location in presence of outliers, or generally, for unreliable data.

Question 26

Which two methods are most common and most useful when it comes to variability? (Variationsrikedom)

Answer 26

Sample variance and Inter-Quartile Range

Question 27

How do you define the lower (or the first) quartile?

Answer 27

You may define lower (or the first) quartile Q_1 to be the value such that one quarter of data lie below it and 3 quarters – above it.

Question 28

How do you define the upper (or the third) quartile?

Answer 28

the upper (or the third) quartile Q_3 is the value such that 3 quarters of data lie below it and 1 quarter – above it.

Question 29

How do you define Inter-quartile range?

Answer 29

IQR = Q3 − Q1, where

Q1, Q3 are the lower and upper quartiles, respectively.

Question 30

How does IQR react on outliers?

Answer 30

IQR is robust (insensitive) to outliers.

Question 31

What do you need to use Five Figure Summary?

Answer 31

L, Q_1, m, Q_3, U, where L is the maximum of ( smallest observation and Q_1-1.5IQR) and U is the minimum of (largest observation and Q_3+1.5IQR)

Question 32

If U = Q_3 + 1.5(IQR) or/and L=Q_1 −1.5(IQR) what happends to the values above/below?

Answer 32

They get noted as outliers.

Question 33

When do you use a boxplot?

Answer 33

When you want to display a five figure summary

Question 34

What does the boxes, whiskers and * mark in a boxplot?

Answer 34

A box is drawn with edges at Q1 and Q3. The segment inside shows median m. Additional lines (whiskers) represent the range of the lower 25% of data and of the upper 25% of data excluding outliers. The outliers are marked separately with *. In principle, each section of the plot corresponds to 1/4 of data so the plot also gives immediate info about the shape of the distribution.

Question 35

When the distribution is skew, what is better to use, mean or median?

Answer 35

Then the median is a much better typical value than the mean

Question 36

What is the relation between Sampla variance and standard deviation?

Answer 36

(Standard deviation)^2=Sample variance