Types of Data & Statistical Analysis (Final Exam)

Question 1

What are the two main categories of data?

Answer 1

1. Quantitative data

2. Categorical data

Question 2

What are the two sub-types of Quantitative data?

Answer 2

1. Continuous

2. Discrete

Question 3

Which sub-type of data discussed considers all values possible within a range? (i.e. shear strength of porcelain)

Answer 3

Continuous Quantitative data

Question 4

Which sub-type of data discussed considers only certain values possible in a range? (e.g. number of decayed teeth a person has–possible values 0-32)

Answer 4

Discrete Quantitative data

Question 5

What are the two sub-types of Categorical data?

Answer 5

1. Nominal

2. Ordinal

Question 6

What sub-type of data discussed involves data falling into a category, but there is no order to the data? (e.g. presence/absence of oral cancer, or race/ethnicity)

Answer 6

Nominal Categorical data

Question 7

What sub-type of data discussed involves data that has specific order to it? (i.e. Never, Few times/month, Few times/week, Every day)

Answer 7

Ordinal Categorical data

Question 8

In what 4 ways is Quantitative data is described as?

Answer 8

1. Mean
2. Median
3. Mode
4. SD

Question 9

What type of Quantitative data is sensitive to extreme values?

Answer 9

Mean

Question 10

What type of Quantitative data is less sensitive to extreme values?

Answer 10

Median

Question 11

In what the 2 ways Categorical data is described as?

Answer 11

1. Frequency

2. Percentage

Question 12

What type of Categorical data is the count of a given outcome or in each category?

Answer 12

Frequency

Question 13

What type of Categorical data is the count of a given outcome per hundred showing proportion of each category out of the total?

Answer 13

Percentage

Question 14

Which letter is representative or Correlation?

Answer 14

r

Question 15

What is the square of correlation (r^2) representative of?

Answer 15

The fraction of variation in Y explained by X.

Question 16

The ____ the r^2, the better the fit of the regression line is.

Answer 16

Higher

Question 17

“Usually states there is no difference between two groups being compared or no effect of a product or intervention; u1=u2”

Answer 17

H0: Test Hypothesis (null)

Question 18

“Usually states that there IS a difference between two groups being compared or an effect of a product or intervention; often the one the researcher thinks is the “truth”.”

Answer 18

Ha

Question 19

In a directional hypothesis, u1 ___u2

Answer 19

>

Question 20

In a non-directional hypothesis, u1 ____u2

Answer 20

Does NOT equal

Question 21

What type of error involves rejecting the null hypothesis that is actually true in the population?

Answer 21

Type I Error

Question 22

Which letter describes the level of statistical significance and is interpreted as the maximum chance of incorrectly rejecting the null hypothesis when it is actually true?

Answer 22

Alpha

Question 23

What type of error involves failing to reject (accept) the null hypothesis that is actually false in the population?

Answer 23

Type II Error

Question 24

Which letter describes the probability of a type II error?

Answer 24

Beta

Question 25

Power is calculated as _____ and is related to the sample size used in the study.

Answer 25

1-Beta

Question 26

"The probability, assuming that the null hypothesis is true, of seeing an effect as extreme or more extreme than that in the study by chance."

Answer 26

P-value

Question 27

If the P-value is less than or equal to Alpha, what does this indicate?

Answer 27

You should reject the null hypothesis.

Question 28

If the P-vaue is greater than Alpha, what does this indicate?

Answer 28

You should fail to reject the null hypothesis

Question 29

"A range of values about a sample statistic that we are confident that the true population parameter lies"

Answer 29

Confidence Intervals

Question 30

Researcher's commonly set Confidence Intervals at ____%.

Answer 30

95%

Question 31

How are Confidence Intervals interpreted?

Answer 31

If the data collection and analysis is repeated over and over, the CI will include the correct value 95% of the time.

Question 32

"Statistical test that can be used to determine whether the mean value of a continuous outcome variable differs significantly between two independent groups (i.e. comparing the mean years of survival for implants in women vs. men to see if they differ significantly)"

Answer 32

T-test

Question 33

What type of test assumes approximate normal distribution of the variable of interest in the groups being compared?

Answer 33

T-test

Question 34

The __________ can be used when the outcome variable of interest is only being examined in one group (testing difference from 0 or some given value).

Answer 34

One-Sample T-test

Question 35

The __________can be used when subjects are matched in pairs and their outcomes are compared within each matched pair (including where observations are taken on the same subjects before and after a given intervention).

Answer 35

Matched-Pair T-test

Question 36

When comparing categorical data, the _______ test can be used to compare the proportion of subjects in each of two groups who have a dichotomous outcome (i.e. comparing the presence of periodontitis in diabetics vs. non-diabetics)

Answer 36

Chi-squared test

Question 37

_____ is a, "statistical method that allows for comparison of several population means"

Answer 37

ANOVA (analysis of variance)

Question 38

ANOVA uses the _____ statistic in relation to alpha to determine whether of not the null hypothesis should be rejected or not.

Answer 38

F-statistic

Question 39

A study that compares the strengths of composite A, B and C to see if they are significantly different would be referred to as?

Answer 39

ANOVA (analysis of evidence)

Question 40

"Situation in which a non-casual association between a given exposure and an outcome is observed as a result of the influence of a third variable."

Answer 40

Confounding (usually designated a confounding variable or confounder).

Question 41

A variable is a confounder if:

Answer 41

1. It is a known risk factor for the outcome | 2. It is associated with the exposure but is not the result of the exposure

Question 42

How to do you evaluate if a covariate is a confounder?

Answer 42

1: Is it associated with exposure? 2: Is it casually associated with outcome? If YES, then: Step 1: Calculate Crude Association Step 2: Calculate stratum specific association

Question 43

_____ can lead us to conclude a casual relationship, when in fact, there is none or vice versa.

Answer 43

Confounding (confounding is NOT an "all or none" phenomenon"