Exam 2

Question 1

What is descriptive research?

Answer 1

characterizing the sample or data
- average age of students in the class, highest/lowest marks

Question 2

What is inferential research?

Answer 2

trying to reach conclusions that extend beyond the immediate data alone
- make judgements of the probability that an observed difference between grips is a dependable one
- used when you can’t measure everyone or everything

Question 3

What are the 3 scales of measurement?

Answer 3

Nominal, ordinal, continuous

Question 4

What is a nominal scale?

Answer 4

unordered data, no ranking
- can’t calculate a mean
- ex. sex, favourite colour, breed of dog

Question 5

What is an ordinal scale?

Answer 5

predetermined order among response classification
- can’t take an average
- ex. education level, placing in race

Question 6

what is a continuous scale of measurement? (interval/ratio)

Answer 6

most precise, can get a mean

Question 7

What are statistics?

Answer 7

an objective way of understanding our data

Question 8

What 2 things do statistics inform us of?

Answer 8

• reliability
  -significance (is this due to chance?) and meaningfulness (does this matter in the real world

Question 9

What is central tendency?

Answer 9

single score that best represents all scores for a group of individuals
- Mean - most common measure of CT
- Median - number occurring at the midpoint of the series
- Mode - most frequently occurring number

Question 10

What is a normal curve or normal distribution?

Answer 10

Characterized by symmetrical distributing of data about the centre of the curve
- Mean, median and mode all located at middle of curve
- frequency of scores decline in a predictable manner as scores deviate further from the centre of the curve

Question 11

What is variability?

Answer 11

Measure of spread or dispersion of data
- how spread out the data is
- deviations from the mean
- used to know whether data is closely collected around the mean or not

Question 12

What is standard deviation?

Answer 12

measure of spread
- how spread out the data is from the mean
- How much variability there is in the data

Question 13

What is the difference between low standard deviation and high?

Answer 13

Low - data was closely clustered around the mean
High - data is dispersed around a larger range of values

Question 14

How does standard deviation impact large data sets?

Answer 14

• 68% of data is within 1 SD
• 95% of data is within 2 SD
• 99% of data is within 3 SD

Question 15

What is skewness?

Answer 15

Describes direction of hump and nature of the tails
- positively skewed - hump to left, tail to right (mean is higher than median and mode)
- negatively skewed - hump to right, tail to left (mean is lower than median and mode)

Question 16

What is kurtosis?

Answer 16

describes vertical aspect of curve
- used to describe the degree to which scores cluster in the tails or peak of a frequency
- Leptokurtic curve - high kurtosis have distinct peak near mean and decline rapidly, have heavy tails
Platykurtic curve - low kurtosis tend to have flat top near mean
Mesokurtic curve - normal distribution

Question 17

What is the basis of community engaged research? (5)

Answer 17

• not usually done in a lab
• Contributes to academic and community success
• community based organizations have credible, legitimate and intimate understandings of the assets, concerns, values and activities in their community
• Partnership based on both parties having valuable knowledge
• Process of planning a change, acting and observing, reflecting on processes an consequences and re-planning

Question 18

What is a community?

Answer 18

Group of people linked by social ties who share common perspectives or interests, and may share a common geographical location
- Not homogenous and seldom speak with a single voice

Question 19

Why do we use community- engaged research? (5)

Answer 19

• Increasing interest in health disparities in diverse communities
• Challenging health and social problems can’t be answered by experts alone
• Disappointing results with introducing evidence based practices in real world
• Increasing community desire for collaboration, not just research on a group
• Increasing funder interests in community-driven versus community-placed research

Question 20

What are barriers with community-engaged research? (6)

Answer 20

• researchers aren’t connected to community organizations or diverse communities
• community organizations don’t realize they can collaborate with researchers (no cost)
• takes time and money
• researchers need peer reviewed papers for their career
• researchers have to give up some control to community partners
• poor communication and unrealistic expectations can lead to conflicts between academic and community partners

Question 21

How to combat survey fatigue? (5)

Answer 21

• exhaustive vs. exhausting
• expectations - “Survey will take approx. 10 mins”
• know your audience - invested in topic makes people more likely to finish survey
• open (written answers) vs. closed (on a scale, multiple choice)
• relationship of the respondent or topic

Question 22

What is important about the wording of surveys?

Answer 22

using grade 10 literacy levels, not using highly technical language, clear, short and easy to understand

Question 23

How many questions can you ask at once on a survey?

Answer 23

1

Question 24

How do you order questions on a survey?

Answer 24

Group similar topics assuming it doesn’t cause other issues
- leave questions that may cause offence to be very personal to the end (reduce bias in earlier responses or leaving survey)
- Logic flow (design rules that dictate what questions will come after one another)

Question 25

What is prompting or priming in a survey?

Answer 25

exposure to a topic, stimulus or idea which then biases how they answer future questions

Question 26

What are the 4 types of bias?

Answer 26

referral, recall, confirmation, healthy worker effect

Question 27

What is referral bias?

Answer 27

referred from a certain group of people
ex. diabetes survey - get all participants from same clinic, won’t necessarily reflect entire population

Question 28

What is the healthy worker effect?

Answer 28

People who work are healthier than those who don’t

Question 29

How can you ask sensitive questions? (4)

Answer 29

• normalize - “in talking to people we’ve found people often have too much work to exercise regularly. how often do you exercise?”
• re-affirm it is an opinion - “In your opinion…”
• Other people approach - “do you know of anyone who…”
• recognize measurement error will be an issue

Question 30

What are inferences?

Answer 30

Can be made from sample to population only is you use a confidence interval or p value

Question 31

What is a confidence interval?

Answer 31

How accurate the measurement is likely to be
- population with lots of variability leads to large CI
- larger samples tend to give us more info and we can be more sure of our estimate - lead to smaller CI
- estimated value of population parameter, indicates precision, narrow CI indicates more confidence

Question 32

What is a P-value?

Answer 32

determines statistical significance in hypothesis test
- how likely it is to get a result like this is null hypothesis is true
- attempts to show that no variation exists between variables or that a single variable is no different than 0
- low p-value suggests data is inconsistent with the null, favouring an alternative hypothesis

Question 33

What is a null hypothesis?

Answer 33

nothing happens, no difference

Question 34

What is an alternative hypothesis?

Answer 34

change is assumed

Question 35

What is a type I error?

Answer 35

falsely assume you can reject the null hypothesis and that the alternative hypothesis is true
- also called false positive result
- incorrect rejection of null hypothesis
- usually leads one to conclude that a supposed effect or relationship exists when it doesn’t
- can’t be completely avoided but investigators should decide on an acceptable level of risk when designing research

Question 36

What is an example of a type 1 error?

Answer 36

Test shows patient to have a disease when they don’t

Question 37

What is a type II error?

Answer 37

falsely assume you can reject alternative hypothesis and null hypothesis is true
- false negative result
- failure to reject a false null hypothesis
- leads to conclusion that an effect or relationship doesn’t exist when it does

Question 38

What is significance in quantitative data?

Answer 38

odds observed result is die to chance
- don’t want this - set it low

Question 39

What is power in quantitative data?

Answer 39

• probability of rejecting the null hypothesis while it is false (avoiding type II error)
• ranges from 0 to 1
• greater the power the more likely you are to detect a real difference or relationship
• odds you will observe a treatment effect when it occurs
• you want this - set it high

Question 40

What is the most commonly used p-value?

Answer 40

0.05

Question 41

What does a low p-value mean?

Answer 41

data is inconsistent with the null, favouring an alternative hypothesis

Question 42

What is effect size in quantitative data?

Answer 42

shows that an effect was large enough to rule out null hypothesis
- effect size is independent of sample size
- tells you meaningfulness of the results
- large effect size means there is a strong relationship

Question 43

What is Cohen’s d?

Answer 43

measures size of difference between 2 groups

Question 44

What is Pearson’s r?

Answer 44

strength of relationship between 2 variables

Question 45

What is a between subjects design?

Answer 45

different people test each condition, each person is only exposed to a single user intervention
-prevents carryover effect (lingering effects of being on 1 experimental condition on a subsequent condition
- shorter duration
- requires more participants and resources
- individual differences may threaten validity

Question 46

What is a within subject design? (repeated measures)

Answer 46

same people test all the conditions
- requires fewer participants
- no variations in individual differences
- carryover effects - first test influences the other