Lecture 1

Question 1

Define Statistics

Answer 1

Technique where data’s organized, treated, & presented for interpretation

Question 2

Reasons Why Statistics are Useful?

Answer 2

1.) Calculating probabilities
2.) Comparing things from same group
3.) Determine how treatment affects outcomes
4.) Likelihood of making a wrong conclusion (type 1 error)
5.) determine strength of conclusion-supporting evidence

Question 3

How are Statistics used?
4 ways

Answer 3

1.) to determine best treatments
2.) to make clinical diagnoses
3.) to form tests & theories
4.) to make evidence-based decisions

Question 4

What is Measurement?

Answer 4

Process of comparing a value to a standard

Question 5

What are 4 types of Measurements used in stats?

Answer 5

1.) Distance - eg; height, long jump distance
2.) Force - eg; body weight, isometric strength
3.) Time - eg; # of seconds to complete 100m race
4.) Frequency - eg; heart rate in beats per minute

Question 6

2 things that make a good measurement?

Answer 6

1.) Reliability
2.) Validity

Question 7

What is Reliability?

Answer 7

Reproducibility & consistency

Question 8

What is Validity?
- provide an example

Answer 8

Test measures what it is designed to measure
- often a correlation from 1 test to another
- eg; 6-min walk test for VO2Max estimation

Question 9

What are Variables?

Answer 9

Characteristics of a person, place, or object that can assume more than one value
- includes; anthropometric & performance outcomes

Question 10

What are Constants?

Answer 10

Characteristics that do not change
- eg; competition distances, weight categories…

Question 11

What are the 3 types of Measurement Scales we will be using?

Answer 11

1.) Ordinal
2.) Interval
3.) Ratio

Question 12

What is the Ordinal Measurement Scale?
- defining characteristic & example

Answer 12

scale ranks participants/objects
- Eg; rankings in sport (doesn’t tell you how much someone is better by)

Question 13

What is the Interval Measurement Scale?
- defining characteristic & example

Answer 13

Equal units of measurement with no true 0 (eg; 0 degrees C doesn’t mean there is no temperature)
- eg; temperature

Question 14

What is the Ratio Measurement Scale?
- defining characteristic & example

Answer 14

Scale has an absolute 0 (0=absence of value)
- eg’ weight, distance, marks on exams, etc.

Question 15

What is a Theory?

Answer 15

A belief regarding a concept or series of related concepts
- generate hypotheses to be tested
- eg; gravity, evolution, sliding filament theories
- theories derive from hypotheses that survive testing

Question 16

What is a hypothesis?

Answer 16

Something that must be testable & falsifiable
- not 100% correct 100% of the time

Question 17

What is a Null Hypothesis?

Answer 17

H0 = a hypothesis opposite to the real hypothesis

It is the hypothesis you are trying to reject

Question 18

What are 3 different types of research design?

Answer 18

1.) Historical
2.) Observational
3.) Experimental (associated with science)

Question 19

Hypothesis Testing - 2 ways this can be done

Answer 19

Hypothesis testing uses a research/alternative hypothesis and a null hypothesis
- can be directional or non-directional

Question 20

Directional vs Non-Directional Hypothesis Testing

Answer 20

In directional tests you hope to see a change in a specific direction (preference on what the outcome is)

In Non-Directional tests something will happen but unsure of what (+’ve or —‘ve)

Question 21

Review Hypothesis percentiles slides**

Question 22

What are Independant Variables?
- 3 examples

Answer 22

Variable that can be changed or adjusted
- eg; height, exercise program, & type of lacrosse stick

Question 23

What are Dependent Variables?
- 3 examples

Answer 23

Variables that you measure & cant be changed
- eg; points per game, 1RM max, throwing accuracy

Question 24

How are dependent and independent variables related?

Answer 24

Independent variables determine the outcome of dependent variables
- as practice increases (IV)… skill increases (DV)

Question 25

What is Internal Validity?

Answer 25

Control in experiment to make sure results are due to treatment
- assessment of quality of experimental control
- common techniques = control/placebo conditions, randomization, & blinding

Question 26

When discussing Internal Validity, what are Intervening (extraneous) Variables?

Answer 26

Fatigue or learning effects from repeated testing

Question 27

When discussing Internal Validity, what is Instrument Error?

Answer 27

Poor calibration or loss of calibration

Question 28

When discussing Internal Validity, what is Investigator Error?

Answer 28

Error in skinfold technique, data entry errors, etc

Question 29

What is External Validity?

Answer 29

Ability to generalize results of an expirament to the population from which the samples were drawn

Question 30

What are a couple questions to consider when discussing external validity?

Answer 30

1.) How well does the sample reflect the population of interest?
2.) Are sample results from college athletes generalizable to professional athletes?
**tight experimental control may make study unrealistic in real world

Question 31

Define Population

Answer 31

Any group of persons, places, or objects that have atleast one common characteristic

Question 32

What is a Sample?

Answer 32

A subset of a population
- you need samples that are representative of the population of interest
- random sample = each member of population has = opportunity of being selected into the sample

Question 33

What is Bias in a Sample?

Answer 33

extraneous factors operate on the sample to make it unrepresentative of the population

Question 34

What is a Parameter?

Answer 34

A characteristic of the population

Question 35

Define Statistics

Answer 35

A characteristic of a sample that is used to estimate the value of the population parameter