Introduction to statistics - Data

Question 1

Data collection techniques

Answer 1

• Observations
• Tests and assessments
• Surveys
• Document analysis (published articles)
• Interviews

Question 2

What are Secondary data?

Answer 2

data that someone else has collected

Question 3

What are Primary data?

Answer 3

data that you collect.

Question 4

Secondary Data Sources

Answer 4

• Country & local city departments -> e.g.,
  Ministère-Direction de la Santé, STATEC (Statistic portal of Luxembourg)
• Hospitals, Clinics & Schools
• Research institutions e.g., Luxembourg Institute of Health
• Journal Articles
• International institutions e.g., OECD

Question 5

Secondary Data disavantages

Answer 5

• May be out of date for what you want to analyze.
• May not have been collected long enough for detecting trends.
• There may be missing information on some observations
• May be incomplete
• You have no control over data quality

Question 6

Secondary data advantages

Answer 6

• Saves time
• Saves money
• Easily Accessible
• Increases the feasibility of multicenter/ international collaboration

Question 7

Challenges of primary data

Answer 7

• Can be expensive to collect
• Selection of population or sample
• Difficulty recruiting participants
• Pretesting/piloting the instrument to determine the presence or absence of measurement bias

Question 8

Who/What do we collect data from?

Answer 8

1. Patients
2. Therapists
3. Published research
4. Electronic devices
5. Public & Private organisations
6. Anything that exists can be a source of data

Question 9

Defenition Population

Answer 9

A population is a group (e.g. patients) that have something in common (e.g. back pain).
(-> Target population)

Question 10

Defenition Sample

Answer 10

A sample is a smaller group with similar characteristics from within that population.

Question 11

What’s a sample bias?

Answer 11

When the sample shows a higher % of a special caractéristics, or a type of person compared to the % in the population

Question 12

Which are the probalistic sampling methods?

Answer 12

• simple random
• statified random
• systematic random
• clustered random

Question 13

Non probabilistic sampling methods?

Answer 13

• convenience
• purposive
• snowball

Question 14

What are descriptive statistics used for?

Answer 14

• summarise data
• describe data
• present data

Question 15

Types of descriptive statistics

Answer 15

1. Measures of Frequency
2. Measures of Centeal Tendency
3. Measures of Dispersion or variability
4. Measures of position & rank

Question 16

Measures of Frequency

Answer 16

Count, Percent & Frequency
Shows how often an observation occurs.

Question 17

Measures of Centeal Tendency

Answer 17

Mean, Median & Mode
-> Locates the distribution by variouspoints.
-> Shows the average or the most common score.

Question 18

Measures of Dispersion or variability

Answer 18

Range, Variance, Standard Deviation & Interquartile Range.
- Identifies the spread of scores by stating intervals
- Range = high/low points in the dataset
- Variance or Standard Deviation = difference between observed score and the mean
- Shows how “spread out” the data are. It is helpful to know when data are spread out as this can affect the average.
- The Interquartile range is the difference between the third quartile and the first quartile.

Question 19

Measures of position & rank

Answer 19

Percentile Ranks, Quartile
-> Describes how scores fall in relation to one another. Relies on standardized scores
-> Compares scores to a normalized score (e.g. a national norm)

Question 20

Mean

Question 21

By what can be affected the Mean?

Answer 21

By outliers
-> can make the mean a bad measure of central tendency

Question 22

What’s the median

Answer 22

When data are listed in order, the median is the point at which 50% of the cases are above and 50% below it.
This is the same as the 50th percentile.

Question 23

What’s the mode?

Answer 23

The observation with the highest frequency

Question 24

What’s the range?

Answer 24

The range is the difference between the lowest value and the highest value in a dataset

Range = (maximum value – minimum value)

Question 25

What’s Q1?

Answer 25

=1st Quartile
= the value occupying the ¼ position of all values arranged in ranked order. Or median of the 1st half of all observations.

Question 26

What’s Q3?

Answer 26

= 3rd quartile
= the value occupying the ¾ position of all values arranged in ranked order. Or the median of the 2nd half of all observations.

Question 27

What’s IQR?

Answer 27

= Interquartile = Q3-Q1

Question 28

What’s Q2?

Answer 28

= median

Question 29

Variance

Answer 29

= is a measure of how close together or far apart the values in a databest

->The larger the variance, the further the individual values are from the mean.

->The smaller the variance, the closer the individual values are to the mean.