ST 311 Chapter 1 Notes

statistics

the science of planning studies and experiments, obtaining data, organizing, summarizing, analyzing and interpreting those data and then drawing conclusions based on them.

1. Prepare- consider the population, data types and sampling method

2. Analyze- describe the data you collected and use appropriate statistical methods to help with drawing conclusions

3. Conclude - Using statistical inference, make reasonable judgements and answer broad questions

Data

Collections of observations, such as measurements, counts, descriptions or survey responses.

Population

The complete collection of all measurements or data that are being considered.

Population of interest

The specific population that we would like to better understand or describe.

Sample

Subset of members selected from a population

• for good results samples should be random and representative of the population

Parameter

a numerical measurement describe some characteristic of a population

Statistic

a numerical measurement describing a characteristic of a sample

Quantitative Data

consists of numbers representing counts or measurements…. aka numerical data

Discrete Quantitative Data

number values are finite and countable

continuous quantitative data

results from infinitely many possible quantitative values… uncountable

Bias

samples that are more likely to produce some outcomes than others… not true representation

convenience bias

easy to collect often are not representative of a full population.

• ex. standing at a corner and collecting samples

volunteer bias

self selected participants that tend to all lean a certain way.

Simple Random Sample (SRS)

sample of “a” subjects selected in a away that every possible sample of the same size(n) has the same probability of being chosen

stratified sample

subdivides the population into at least 2 groups that have a common characteristic (age, height, ethnicity etc.) called strata then a sample is drawn from each strata proportionate to the amount that the population represents.

Cluster Sample

Dividing the population into naturally occurring sections then randomly selecting entire clusters and choosing all members from these selected clusters.

Systematic Sample

Randomly assign numbers to subjects, then select random starting point, then every kth element in the list. … every 3rd x

Bad sampling frame (bias)

when the sample gathered isnt representative of the whole population.

Undercoverage

bad sampling frame

sampling methods

assign members of the population to the sample

randomization methods

assigns members of the sample different treatment groups, sections, etc to the experiment

non response bias

some of the sample/population did not response

wording order

the way that the questions were worded and the order of the questions can sway the participant to answer in different ways.

mean

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