Statistics 1

Question 1

Population

Answer 1

Everyone/everything we are getting a sample from.

Question 2

Sample

Answer 2

A subset of the population.

Question 3

Census

Answer 3

Testing an entire population. Not sampling.

Question 4

Descriptive Statistics

Answer 4

The process of summarizing and presenting the sample data in a condensed form.

Question 5

Inferential Statistics

Answer 5

The process of generalizing from our sample data to draw conclusions about our population.

Question 6

Numerical Data

Answer 6

Data in the form of numbers (ex. time, distance, amount).

Question 7

Categorical Data

Answer 7

Data in the form of categories (ex. type, yes or no).

Question 8

Continuous

Answer 8

Numerical data that can take on an entire range of values (ex. time, lengths).

Question 9

Discrete

Answer 9

Numerical data that has a restricted amount of values (ex. dollars).

Question 10

Univariate

Answer 10

A single set of numerical data.

Question 11

Bivariate

Answer 11

A paired set of numerical data.

Question 12

Bar Graphs

Answer 12

Display for categorical data.

Question 13

Frequency (Bar Graphs)

Answer 13

Displaying the number of __.

Question 14

Relative Frequency (Bar Graphs)

Answer 14

Displaying the % of a category. Demonstrating proportions.

Question 15

Dot Plots

Answer 15

Number lines with small dots above data values.

Question 16

Observational Study

Answer 16

Study where the investigator collects data. The easiest and most common way to collect data.

Question 17

What can you draw from an observational study?

Answer 17

You can draw conclusions about a single population or compare two populations.

Question 18

Experiment

Answer 18

Where the investigator actively manipulates the subjects.

Question 19

Experimental Units

Answer 19

Subjects being tested.

Question 20

What can you draw from an experiment?

Answer 20

You can draw a “cause and effect” relationship.

Question 21

Random Selection

Answer 21

Selecting a sample from your population at random.

Question 22

Random Assignment

Answer 22

Randomly selecting people from your sample and putting them into different treatment groups.

Question 23

Simple Random Sampling

Answer 23

Get all names from population and choose your sample in a random way from the list (ex. put in hat, shake, pick).

Question 24

Stratified Random Sampling

Answer 24

If population is naturally split into subgroups and you want to represent each group proportionately, sample each group separately.

Question 25

Cluster Sampling

Answer 25

Pick a group at random rather than picking individuals. The group must still be representative of the population.

Question 26

Systematic Sampling

Answer 26

After picking 1st person of a randomly ordered list, choose every Kth person.

Question 27

Convenience Sampling

Answer 27

Badness - Picking whoever is nearby and easy.

Question 28

Selection Bias

Answer 28

Systematically excluding a part of a population.

Question 29

Measurement Bias (response bias)

Answer 29

They way you collect data is the problem.

Question 30

Non Response Bias

Answer 30

When you don’t get responses from the chosen sample.

Question 31

Treatments

Answer 31

Different experimental conditions being compared.

Question 32

Explanatory Variable

Answer 32

Explains the variation between the group. The possible values of the treatment.

Question 33

Response Variables

Answer 33

The possible values of the result that you are measuring.

Question 34

Replication

Answer 34

The use of more than one subject or operation for each treatment group.

Question 35

*The purpose of random assignment is __

Answer 35

to create roughly equal treatment groups on extraneous variables, so the only difference is the treatment.

Question 36

Direct Control

Answer 36

Variables that the experimenter directly manipulates or controls.

Question 37

*The purpose of direct control/blocking is __

Answer 37

to reduce variability so that differences can be more easily seen.

Question 38

Control Group

Answer 38

An experimental group which receives no treatment.

Question 39

Confounding Variable

Answer 39

A variable related to both the treatment and the response variable. If you have it, you can’t tell if the treatment effects are due to treatments or another factor.

Question 40

Blocking

Answer 40

The formation of groups of subjects that are similar (ex. conducting one experiment for girls and one for boys).

Question 41

Completely Randomized Experiment

Answer 41

The most common type of experiment. Randomly assigning subjects to their treatments.

Question 42

Matched Pairs Experiment

Answer 42

(don’t work for all experiments) Either pairing alike subjects and randomizing treatments, or giving both treatments to single subject in random order.