Session #6 Flashcards Preview

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Flashcards in Session #6 Deck (40)
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1
Q

what are the two types of quantitative data?

A

continous

discrete

2
Q

type of quatintative data in which all values are possible in a range

A

continuous

ex: shear strength of porcelain

3
Q

type of quantitative data in which only certain valuess are possible in a range

A

discrete

ex: possible number of teeth someone has

4
Q

what are the two types of categorical data?

A

nominal

ordinal

5
Q

type of categorical data where data falls into category, but no order to data

A

nominal

ex. presence/absence of oral cancer, or race/ethnicity

6
Q

type of categorical data where that has a specific order to it

A

ordinal

how often do you brush your teeth? (never, seldom, always)

7
Q

which is more sensitive to extreme values, the mean or the median?

A

mean

8
Q

measure of how much the individual data points vary around the MEAN

A

standard deviation

9
Q

describing if there is a linear relationship btw an independent variable (X) and a dependent variable (Y)

A

correlation

10
Q

the value of a correlation coefficient lies between what numbers?

A
  • 1 and 1

* the closer (r) is to 1 or -1 the stronger the relationship

11
Q

the fraction of variation in Y explained by X

A

square of the correlation

the higher the r-squared the better the fit of the regression line

12
Q

an explanation of certain observations

A

hypothesis

13
Q

what do we use hypothesis testing for?

A

to tell if what we observe in the population is consistent with the hypothesis

14
Q

what is the null hypothesis?

A

states that there is NO DIFFERENCE btw two groups being compared or NO EFFECT of a product or intervention

15
Q

what is the alternative hypothesis?

A
  • this is the one the researcher thinks is the “truth”
  • states that THERE IS A DIFFERENCE btw two groups being compared or an effect of a product or intervention

can be directional or non-directional

16
Q

the population mean for group 1 is the same as the population mean for group 2

A

H0 interpretation

17
Q

the population mean for group 1 is different than the population mean for group 2

A

Ha interpretation

18
Q

type 1 error

A

rejecting the null hypothesis that is actually true in the population

19
Q

the level of statistical significance (alpha) is commonly set to _____ and is interpreted as what?
***this is only in type I errors

A
  • o.o5

- the max chance (5%) of incorrectly rejecting the null hypothesis when it is actually true

20
Q

type II error

A

failing to reject the null hypothesis that is actually false in the population

21
Q

beta

A

the probability of type II error

22
Q

power

A

1-B and is related to the sample size used in the study

23
Q

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

A

p-value

  • reject the null hypothesis is P-value less than or equal to alpha
  • fail to reject if P-value is more than alpha

—-the higher the p-value, the more leeway you are giving yourself to be wrong by chance

24
Q

a range of values about a sample stat that we are confident that the true pop parameter lies

A

confidence interval

most common = 95%

25
Q

statistical test that can be used to determine whether the mean value of continuous outcome variable differs significantly between two independent groups

A

t-test

26
Q

type of t-test that can be used when the outcome variable of interest is only being examined in one group

A

one-sample t-test

27
Q

type of t-test that 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 giving and intervention)

A

matched-pair t-test

28
Q

when examining categorical data, this test can be used to compare the proportion of subjects in each of two groups who have a dichotomous outcome

A

chi-squared test

29
Q

statistical method that allows for comparison of several population means

A

ANOVA

***IS USED FOR CONTINUOUS VARIABLES WITH MORE THAN TWO GROUPS

30
Q

what type of statistic does an ANOVA test use?

A

F-statistic

31
Q

Determining if findings are important from a clinical standpoint

A

clinical significance

32
Q

probability that chance is responsible of an observed difference

A

statistical significane

33
Q

does a p-value say anythings about clinical relevance or quality of a study?

A

no

34
Q

what are the main limitations of statistical inference?

A
  • only tells about the role of chance or random error in making inference from your study population to the source populaiton
  • does NOT tell about the role of bias or confounding
  • STATISTICS DO NOT TELL YOU ABOUT CAUSALITY
35
Q

systematic error in design, conduct or analysis of a study that results in a mistaken estimate of an exposure’s effect on disease

A

bias

36
Q

systematic error in selecting subjects into one or more groups, such as cases and controls, or exposed or unexposed

A

selection bias

37
Q

errors in procedures for gathering relevant info

A

info bias

38
Q

situation in which a non-causal association btw a given exposure and an outcome is observed as a result of the influence of a third variable

A

confounding variable

39
Q

what two things make a variable a confounder?

A
  • it is a known risk factor of the outcome

- it is associated with the exposure but is not the result of the exposure

40
Q

is confounding an “all or none” phenomenon?

A

no