Basic Statistics

Question 1

Mode (Moda)

Answer 1

The value that occurs most frequently in a given data set.

Question 2

Interquartile Range (IQR)

Answer 2

Rozstęp ćwiartkowy
Q3-Q1

Question 3

Standard Deviation (SD)

Answer 3

Odchylenie standardowe: sqrt(variance)

Question 4

Variance

Answer 4

Population: (mean - xi)^2 / N where xi is each element of set

Sample: Use n - 1 instead

Question 5

How to describe a histogram

Answer 5

4 Main Aspects:

• Shape - Overall appearance of histogram. Can be symmetric, bell-shaped, left skewed, right skewed, etc…
• Center - Mean or Median
• Spread - How far our data spreads. Range, Interquartile Range (IQR), standard deviation, variance.
• Outliers - Data points that fall far from the bulk of the data.

Question 6

Study design and types of study

Answer 6

Encompasses everything in preparation for data-driven research process.

Types:

• Confirmatory: Specify falsifiable hypothesis, then test it.
• Exploratory: Collect and analyze data without first pre-specifying question.
• Comparative: contrast one quantity to another.

Question 7

Dependent (example when) vs. Independent Data

Answer 7

• Dependent data observations correlated due to feature of study design (cluster sampling or longitudinal measurement).
• Independent data observations completely independent of each other may/may not arise from common distribution.

Question 8

i.i.d.

Answer 8

i = independent

id = identically distributed

Question 9

Simple Random Samples (SRS)

Answer 9

Each sampling unit of a population has an equal chance of being included in the sample.

Question 10

Longitudinal Data

Answer 10

Repeated measures of same variable, collected from same unit over time → likely correlated.

Question 11

Repeated Measures Data: Wide and Long

Answer 11

Wide format: one row per subject, each measure in separate column.

Long format: one row per measurement.

Question 12

Quantitative Variables types

Answer 12

• Continuous - could take on any value within an interval, many possible values.
• Discrete - countable value, finite number of values.

Question 13

Categorical (or Qualitative) Variables

Answer 13

• Ordinal - groups have an order or ranking.
• Nominal - groups are merely names, no ranking.

Question 14

Conducting a Population Census

Answer 14

Gather data from the whole population.

Question 15

Probability Sampling

Answer 15

Probability sampling refers to the selection of a sample from a population, when this selection is based on the principle of randomization, that is, random selection or chance.

Probability of selection for each unit is known.

Types: SRS, Complex (anything beside SRS - cluster, stratification, etc…)

Question 16

Stratification

Answer 16

Population divided into different strata, and part of sample is allocated to each stratum; → ensures sample representation from each stratum, and reduces variance of survey estimates.

Question 17

Clustering

Answer 17

Clusters of population units (e.g., counties) are randomly sampled first (with known probability) within strata, to save costs of data collection (collect data from cases close to each other geographically)

Question 18

Non-Probability Sampling

Answer 18

• Probabilities of selection can’t be determined for sampled units,
• Often cheap
• Examples: opt-in web surveys, volunteers
• Strong risk of sampling bias

Question 19

Pseudo-Randomization

Answer 19

Combine non-probability sample with a probability sample, Estimate probability of being included in non-probability sample as a function of auxiliary information available in both samples,

Question 20

Non-Probability Sampling Calibration

Answer 20

Compute weights for responding units in non-probability sample that allow weighted sampled to mirror a known population.

Example: If we got more responses from females than males (but population is 50/50), then down-weight females and up-weight males.