1) are commonly known as numerical facts
2) is a field of discipline or study
Htets,tics is the art and science of learning from data.
3 main aspects of statistics:
1) Design: Planning how to obtain data to answer questions.
2) Description: Summarizing the obtained data.
3) Inference: Making decisions and predictions based on data.
1.2 - Population vs. Sample
Def’n: A population consists of all elements whose characteristics are being studied.
samAple is a portion of the population selected for study.
e.g. UofA students in this section
A parameter is a summary measure calculated for population data.
A statisticis a summary measure calculated for sample data.
Types of statistics:
Descriptive: methods to view a given dataset.
e.g. averages, histograms
Inferential: methods using sample results to infer conclusions about a larger population.
e.g. t-tests, simple linear regression
4.1 Observation and Experimentation
Def’n: An observational study is a study where a researcher observes characteristics of
subjects in samples from populations of interest.
expAeriment is a study where a researcher applies different treatments to
different subjects and observes the outcomes.
1. Infer to a larger population (Population)
2. Factor causes change in response (Causal)
Both types of study allow for #1, but only a properly designed (and randomized)
experiment allows for #2 to be valid. Experiments are not always feasible.
Def’n: A sampling frame is the list of subjects in the population from which the sample
A random sample is a sample drawn in such a way that each element of the
population has a chance of being selected. If chances are all the same Æ SRS of size n
- e.g. A deck of cards: picking a card is a simple random sample. Moreover,
placing the card back in the deck is a sample with replacement. Otherwise, there is
sampling without replacement. Bias:
- sampling bias: samples differ due to sys