Prob and Stats Unit 2 Vocab (2.1-2.4)

Statistics

The science of collecting, analyzing, interpreting, and presenting data

Descriptive Statistics

Involves the organizing and summarizing of data

Inferential Statistics

Uses data collected from samples and probability to draw reliable conclusions about the population

Individuals

The items of interest

Variables

The charcteristic(s) of the individuals to be examined

Qualitative Data

Data that puts an individual in a group described by some quality

Quantitative Data

Data that is a numerical measurement or is counted

Discrete Variable

Data that can only take on a finite (countable) number of values.

Continuous Variables

Can take on any of the countless (infinite) numbers of values on a number line

Population

All the items (or people) of interest

Census

Collecting data from the entire population

Frequency Table

Shows the number of times or frequency that an characteristic occurs

Relative Frequency Table

Shows the frequency in relation to the total number of items. The relative frequency of a popuation is the same as the probability

Sample

A group of randomly selected items from a population

Percent Error

A value used for determining how close an estimated population (derived from a sample) is to the actual population (found using a census)

Sampling Bias

When the sample varies from the population because of flawed sampling techniques. Does NOT occur naturally

Sampling Error

When the sample varies from the population by chance (only a portion of the populaiton is studied). Also occurs naturally

Simple Random Sampling

All items or individuals in a population have the same chance of being selected

Sampling Frame

The list of individuals from which the sample is selected

Undercoverage

When part of the population is omitted (not in) from the sampling frame

Selection Bias

A flaw in the selection process that could make the sample not reflect the true population

Random Number Table

A collection of random numbers that are grouped together in a way that makes it easy to read

Systematic Sample

It is assumed that the population is already or could be arranged in some natural sequential order

Stratified Sampling

Divides the population into distinct subgroups called strata

Cluster Sampling

A method of selecting a sample based on naturally occurring groups of the population

Convience Sampling

Creates a sample using individuals from population members that are readily available. (Not random)

Nonprobability Sampling

Sampling that does not involve random selection. May or may not represent the population and is more likely to be biased than samples selected at random

Treatment Group

Recieves the actual stuff

Control Group

Recieves a “fake” thing or placebo of the actual stuff

Lurking Variable

Other factors and variables that could be impacting the results of the experiment other than the intended explanatory variable. (ex: age, sex, stress, and metabolic rates, or even just things like desire to lose weight). No data have been collected but has an influence on other variables in the study

Placebo Effect

A physical change that is a result of the patients just believing in the treatment, whether or not the treatment itself is effective

Completely Randomized Experiment

Individuals are assigned to the treatment groups and control groups in a random way

Randomized Block Experiment

Individuals are grouped or blocked based on a common characteristic (ex: age, race, gender etc)

Response Bias

Results from flaws in the data collection process

Double-Blind Experiment

Neither those conducting the experiment nor the individuals involved in the experiment know if the individual is in the treatment or control group

Observational Study

No treatment is imposed on the individuals

Correlation

There is a relationship between

Causation

One causes the other or causes a change in the other variable

Simulation

An imitation of a situation or process

Parameter

If the numerical measure describes a population

Statistic

If the numerical measure describes a sample

Mean

The average of a data set ( add up all the values in the data set then divide by sample size)

Median

The average of the one or two numbers found in the middle of the data set

Mode

What number(s) reoccur the most

Simple Mean

Take all the numbers, add them up, and divide by the total number of items or individuals

Weighted Mean

Some values contribute more to mean than others

Central Tendency