1 Exploring and understanding Data

Question 1

What makes a bad graph?

Answer 1

1. Not using the correct graph
2. Not using the correct scale
3. Using 3D
4. Using % for unequal sample size
5. Inappropriate Extrapolation
6. Perspective
7. Pie Charts
8. Suppress the origin or change the base line

Question 2

What is causation?

Answer 2

A relationship between two variables foes not mean ‘X causes Y.’

Question 3

What is the problem with averages in statistics?

Answer 3

Average can be affected with one extreme outlier.

Question 4

What is bad sampling?

Answer 4

When the data processing reduces information content of the data. Results extracted from a sample cabbot be better than the sample itself.

Question 5

What are the two reasons we use graphs?

Answer 5

1. Exploration (to find the story of the data)

2. Explaination (to tell the story to an audience)

Question 6

What are the rules for good data visualisation?

Answer 6

1. Use an appropriate graph for your variable type.
2. Check your data
3. Label axes
4. Legend or figure caption
5. Integrity

Question 7

What makes a good graph?

Answer 7

1. Only 2D
2. Do not distort perspective
3. Check you have not exaggerated main features
4. No pie charts
5. Summarise complex data into its simplest understandable form
6. Split the data up if needed
7. Only use lines to join points if continuous data. Leave gaps for missing data.

Question 8

Why have 2 graphs?

Answer 8

You need two graphs if data can’t be adequately expressed in 1 graph.

Question 9

Statistical language: What are Cases?

Answer 9

Cases are the individuals or objects being described.

Question 10

Statistical Language: What is a variable?

Answer 10

A variable is a characteristic of a case.

Question 11

Statistical Language: What is Data?

Answer 11

Data are the observed values of the variables.

Question 12

Statistical Language: What is a Data Set?

Answer 12

A data set contains the observed values of the variables for a group of individuals.

Question 13

Statistical Language: What are cases?

Answer 13

Cases are the individuals or objects being described.

Question 14

Statistical Language: What is a variable?

Answer 14

A variable is any characteristic of a case.

Question 15

Statistical Language: What is Data?

Answer 15

Data are the observed values of the variables.

Question 16

Statistical Language: What is a data set?

Answer 16

A data set contains the observed values of the variables for a group of individuals.

Question 17

What is a census?

Answer 17

A census is an attempt to sample the whole population. (Usually expensive, often logistically impossible)

Question 18

What is a population?

Answer 18

A population is a collection of of all objects/subjects of interest in a study.

Question 19

What is a sample?

Answer 19

A sample is part of the population examined in order to represent the whole.

Question 20

Why do we rely on Samples?

Answer 20

Because a census is almost never practical.

Question 21

What are the three sample ideas?

Answer 21

The three sample ideas are:

1. Sampling - Getting a representative sample.
2. Randomising - Giving everyone a fair chance
3. Sample Size - Sample Size.

Question 22

What is a random sample?

Answer 22

In a random sample, each member of the population has a chance of being selected.

Question 23

What is an SRS?

Answer 23

A simple random sample

Question 24

What are the alternatives to a SRS (Simple random sample)

Answer 24

1. Stratified sampling
2. Systematic sampling
3. Cluster sampling
4. Multistage sampling

Question 25

What is stratified sampling?

Answer 25

Split the population into strata (a group of similar cases such as male and female)

Question 26

What is systematic sampling?

Answer 26

1. Randomly select the first case. 2. Choose every 10th person 3. If 20 cases are to be included in a sample from a population of 100 cases, then - select the first case randomly from the first 5(=100/20) cases (say the 3rd case is detected.) - Systematically take every 5th case ie take the (3+5) = 8th (8+5) = 13th cases etc to obtain a sample of 20 cases.

Question 27

What is multistage sampling?

Answer 27

An example: Take randomly select cities of NSW Then randomly select suburbs in these cities Then randomly select streets in these suburbs Then randomly select the houses in these streets

Question 28

What is cluster sampling?

Answer 28

Cluster sampling is: 1. First select groups (clusters of cases) 2. Then apply a sampling system 3. Then perform a census within each cluster that has been randomly selected 4. Clustering makes he job of sampling easier

Question 29

What is randomising?

Answer 29

Randomising is the use of a number generator to make a selection from a broad population.

Question 30

Why is randomising valuable?

Answer 30

1. Randomising 'averages out' Ny efects we don't know about 2. Randomising 'averages out' any effects we do know about 3. Randomising makes it possible to make decisions about the target population from just a sample.

Question 31

What is Quantitative Data?

Answer 31

Quantitiative data take on numerical values for which mathematical operations (like +,-) make sense. It always has a unit of measurement.

Question 32

What is categorical data?

Answer 32

Categorical data is when the values define the categories. Example: Categorical variables are male/female, faculty etc.

Question 33

What is Ordinal Data?

Answer 33

Data is ordinal if it is categorical data but with a set order. Orften ordinal data is said to be between categorical and quantitative data. Example: responses such as 'disagree', 'neutral' and 'agree' are ordinal.

Question 34

What is identifyer?

Answer 34

Data is an identifyer if it has a unique value for each case in the dataset. Example: tax file number, medicare number, student number. )It does not make sense to summarise an identifyer in a table or graph.)

Question 35

What questions do you ask to understand data?

Answer 35

``` Who What When Where Why How ```

Question 36

What table do you use when you have two categorical variables?

Answer 36

A contingency table (also called Two-way tables or cross-tabulations)

Question 37

What chart do you use when you have 1 variable?

Answer 37

Frequency table.