Module 1

Question 1

Statistics

Answer 1

Field of study involved the science of collecting, describing, and analyzing data

Question 2

Population

Answer 2

Consists fo all individuals or objects of interest; often, the group being studied

Question 3

Sample

Answer 3

A group selected from the population or a subset of the population; provides information used to infer information about populations

Question 4

Why are samples used

Answer 4

Because it difficult getting access to an entire population

Question 5

Question posed to entire STAT250 section:
What is your favorite streaming service?

What is the population?
What is the sample?
Can the sample data be used to make inferences about the population?

Answer 5

Population: All Mason students
Sample: STAT250 students in this section
Can this sample be used to make inferences about the population? Yes & No; Are all students taking a math/logic course as their mason core?

Question 6

What happened when Truman was predicted to lose?

Answer 6

The polls were taken by people (generally wealthier and of a different voting party practice than the entire population) who did not serve as an efficient sample size of the population so the pre-mature prediction was inaccurate.

Question 7

Random Sample

Answer 7

Names in a hat method;
When choosing a simple random sample of n units, all groups of the size n in the population have the same chance of becoming the sample

Question 8

Best ways to do random sampling?

Answer 8

Small group: names in a hat
Large group: technology (random.org, rguroo, statkey, excel)

Question 9

What things might prohibit sampling?

Answer 9

Inability to contact population; cost

Question 10

Non-Random Sample

Answer 10

Targeting a group which may or may not be a conflict on obtaining data

Question 11

Is it possible to successfully gather a random sample without tech?

Answer 11

Nope.

Question 12

Explain Question Wording bias

Answer 12

• Question wording, or confusing or non-neutral language/leading questions;
• inaccurate responses (response bias)
• self-reporting data (usually have strong opinions one way or another)

Question 13

What types of variables are considering during data collection?

Answer 13

Explanatory Variable & Response Variable

Question 14

Explanatory Variable

Answer 14

The variable we think is “explaining” the change in the response variable (usually the variable scientists are manipulating)

Question 15

Response Variable

Answer 15

The variable we think is beign impacted or changed by the explanatory variable; it “responds” to changes in the explanatory variable

Question 16

What is an association relationship between variables?

Answer 16

Two variables are associated if values of one variable tend to be related to values of the other variable

Question 17

What is a causation relationship between two variables?

Answer 17

Two variables are causally related (or associated) if changing the value of the explanatory variable influences the value of the response variable

Question 18

Which of the following statements imply a causal relationship? Also,
think about which are the explanatory and response variables.
a) “Daily Exercise Improves Mental Performance.”
b) “Want to lose weight? Eat more fiber!”
c) “Sales stay the same no matter what medium of advertising is used.”
d) “Goldfish who live in large ponds tend to be larger than goldfish who live in
small ponds.”

Answer 18

a & b have causal relationships

Question 19

Is the following statement a causal or association relationship?

“goldfish who live in large ponds tend to belarger than goldfish who live in small ponds”

Answer 19

Association: Words like “tend to” or “usually” do not imply causation

Question 20

What words do not imply causation?

Answer 20

“tend to” or “usually”

Question 21

What type of variable relationship does the following statement imply?

“Sales stay the same no matter what medium of advertising is used”

Answer 21

Neither causation nor association

Question 22

Identify the explanatory and response variables:

a) “Daily Exercise Improves Mental Performance.”
b) “Want to lose weight? Eat more fiber!”
c) “Sales stay the same no matter what medium of advertising is used.”
d) “Goldfish who live in large ponds tend to be larger than goldfish who live in
small ponds.”

Answer 22

Explanatory variables; Response variables
a) daily exercise; mental performance
b) fiber consumption; weight maintenance
c) advertising; sales
d) pond size; goldfish size

Question 23

T/F An associated between an explanatory and response variable, especially when very strong, always guarantees that the two variables are causally related

Answer 23

False; some variables are associated even when they have no cause and effect relationship

Question 24

Confounding Variable

Answer 24

• A third variable that is associated with both the explanatory and response variable;
• Also called a confounding factor or lurking variable

Question 25

T/F Whenever a confounding variable is present there is a causal relationship

Answer 25

False; a causal relationship cannot be determined when a confounding variable is present

Question 25

Name two methods of data collection

Answer 25

Observational & Experimental

Question 25

Observational Study

Answer 25

A study in which the research does not actively control the value of any variable, but simply observes values as they naturally exist

Question 25

Experiment Collection method

Answer 25

A study in which the researcher actively controls one or more of the explanatory variables; also known as a randomized experiment

Question 26

Explain some characteristics of randomized experiments

Answer 26

- researcher controls the assignment of one or more of the variables - to avoid confounding, the researcher will use random assignment - in a randomized experiment, the value of the explanatory variable for each unit is determined randomly, before the response variable is measured - if a randomized experiment yields an association between the explanatory and response variable, we can establish a causal relationship between these two variables

Question 26

What are some characteristics of observational studies?

Answer 26

- observes individuals and measures variables of interest but does not attempt to influence the responses - often, the researcher is collecting available data after the fact - can almost never be used to establish causation since they almost always possess confounding variables

Question 27

Experimental or Observational Method We contact a random sample of 100 people and record how much each person exercises and also measure the chemicals in the brain of each person.

Answer 27

Observational; no variables were manipulated/controlled/explanatory

Question 28

Experimental or Observational Method: Using a random sample of 100 people, we randomly assign half of them to participate in a regular exercise program for six weeks while the other half makes no changes. At the end of the time period, we measure the brain chemical of each person.

Answer 28

Experimental Method; variables were controlled/manipulated and affected the (response) variables

Question 29

What are three explanations for why an association may be observed in sample data?

Answer 29

1) There is a causal relationship or causal association 2) There is an association, but it is due to confounding 3) There is no actual association; the association seen in the sample data occurred by random chance

Question 30

Evaluating evidence for the causal explanation requires evaluating __________ against the other two competing explanations

Answer 30

evidence

Question 31

What is the best evidence against (2) confounding variables?

Answer 31

the use of random assignment

Question 32

Two main types of randomized experiments

Answer 32

Randomized Comparative Experiment. & Matched Pairs Experiment

Question 33

Randomized Comparative Experiment

Answer 33

Randomizing cases into different treatment groups or a treatment and control groupand then compare results on the response variable

Question 34

Matched Pairs Experiment

Answer 34

Each case gets both treatments in random orer(or cases get paired up in some other obvious way). Then, we examine individual differences in the response variable between the two treatments

Question 35

Four methods for randomization

Answer 35

1) Put all names/numbers in a hat 2) Put names or numbers on cards, shuffle cards, deal out cards into as many piles as there are treatments 3) For the matched pairs experiment, a coin can be flipped to determine which treatment the individual will receive first 4) Use technology (randomize,org, rguroo, statkey)

Question 36

Which method of randomization are the two following: 1) To see if people read faster on paper or a Kindle, one study was done by randomly assigning 16 participants into two groups (paper or Kindle) and timing their reading of a set of instructions. 2) Another study was done in which 16 people read two sets of instructions of similar length, one on a kindle and one on paper. The order in which they read the instructions was randomized.

Answer 36

1) Randomized comparative experiment 2) Matched pairs design; this amkes more sense in this case since individuals reading speed may ary a great deal