Intro (L1) Flashcards
In what case would there be no need for statistics?
If there was no variation in data sets.
Define what is meant by a population……
A complete set of units (e.g. all individuals of a species; all cars in the world) that possess some common characteristic.
Define what is meant by a sample….
A smaller (but hopefully representative) set of units from a population; used to find the true properties about that population.
How do we evaluate a parameter?
By making an estimate from a sample.
What are the symbols for population and sample mean?
Population Mean: μ
Sample Mean: x, y
What are the the symbols for population and ample variance?
Population Variance: σ^2
Sample Variance: s^2
What are the symbols for population and sample standard deviation?
Population Standard Deviation: σ
Sample Standard Deviation: s
Do all samples from the same population have the same mean?
No
What can we do to achieve a better estimate?
Use a larger sample size.
Define what is meant by variable…..
A characteristic or property that is measured on units (e.g. individuals, species): e.g. size, hormone concentration, age, number of genes.
What is the difference between explanatory and response variables?
Explanatory - Expected cause and explains the results.
Response - Expected effect and it responds to explanatory variables.
We try to predict or explain a response variable from one or more explanatory variables.
What is the difference between a numerical continuous variable and a numerical discrete variable?
Numerical Continuous (quantitative): Values within a range and that can be measured.
Numerical Discrete (quantitative): Fixed values and integers that can be counted.
What is the difference between a categorical ordinal variable and a categorical nominal variable?
Categorical Ordinal (qualitative): Data which has an implicit/intrinsic order.
Categorical Nominal (qualitative): Data which has no implicit/intrinsic order but which can be separated into categories.
What is a random sample?
A sample that is random and unbiased where each member of the population has an equal and independent chance of being selected.
What is bias?
A systematic discrepancy between the estimates and the true population characteristic.
