Statistics Final Exam

Front 1

What is the definition of confidence interval?

Back 1

Range of values that has a certain degree of confidence of containing the population parameter -
We don't know the value of the parameter (eg. M mu) but we can estimate it by constructing an interval centered on an observed statistic (eg. x with line on top)

Front 2

Equation for confidence interval

Back 2

CI = x with line on top +/- (zcv) x se

se = standard error of the mean (s/square root of n)

Front 3

what is the only difference between the equivalence of CI's and Hypothesis Test

Back 3

CI gives us an idea of the range within which the mean could occur by chance

Front 4

a form of reactivity whereby subjects improve an aspect of their behavior being experimentally measured simply in response to the fact that they are being studied,not in response to any particular experimental manipulation

Back 4

Hawthorne effect

Front 5

is obtained when moving an element from one set to another set raises the average values of both sets

diseases lead to an idea there was an improvement. changes in methods of diagnoses

Back 5

Will Rogers Phenomenon

Front 6

Use a screening test to identify people with a certain disease, increase in survival due to treatment or intervention because able to diagnose early

Back 6

Zero-time shift or lead-time bias

Front 7

(A special example of selection bias) The set of selective factors that lead hospital cases and controls in a case-control study to be systematically different from one another. This occurs when the combination of exposure and disease under study increases the risk of hospital admission, thus leading to a higher exposure rate among the hospital cases than the hospital controls.

Back 7

Berkson's Bias

Front 8

Use a population approach to deal with health problem that only gives benefit to a small part of population

Back 8

Prevention Paradox

Front 9

Procedures to determine which means differ significantly after a significant f ratio has been found in ANOVA.

Back 9

Post Hoc Multiple Comparison Tests

Front 10

What is the degree of adjustment of critical values that contains a slight adjustment, less control over Type I errors, Increased power (more control over Type II errors)

Back 10

Liberal Adjustment

Front 11

What is the degree of adjustment of critical values that contains Large adjustment, greater control over Type I error, lower power (higher risk of Type II errors)

Back 11

Conservative

Front 12

This is a post Hoc test for equal n that is aslo called Honestly Significant Difference Test (HSD)

Back 12

Tukey Method - designed to make all pairwise comparisons while maintaining alpha sub E at the pre-established alpha level, the test statistic is Q, compare the calculated value of the Q statistic with the critical value

Front 13

This is the ONLY post hoc test that can be used for BOTH pairwise and nonpairwise comparisons

Back 13

Scheffe Method (Complex comparisons)

Front 14

The characteristics of a population are called ____. Represented with GREEK letters, ex: mean of population = mu

Back 14

Parameters
(variance = o2, standard deviation = o)

Front 15

The characteristics of a sample are called ____. Represented with ROMAN letters, ex: mean of sample = x with line on top.

Back 15

Estimates

(variance = s2, standard deviation = s)

Front 16

When we reject a true Ho - when it is falsely concluded that a significant difference exists between the groups being studied

Back 16

Type I Error - denoted by alpha (the probability of making a Type 1 error, it is set before data is collected, also known as rejection region, level of significance, alpha level, alpha = 1 - probability value, chosen by the researcher

Front 17

When we fail to reject a false Ho - when it is falsely concluded that no significant difference exists between populations, when, in fact, a true difference exists

Back 17

Type II Error - denoted by Beta (the probability of making a type II error)

Front 18

Reject Ho and Ho is true

Back 18

Type 1 Error

Front 19

Fail to reject Ho and Ho is false

Back 19

Type II Error

Front 20

If p-value is less than or equal to </= alpha then we

Back 20

reject Ho, the smaller the p-value the more certain you can be that the observed difference in the study is not merely due to chance.

Front 21

if p-value is > alpha then we

Back 21

fail to reject Ho

Front 22

There is a ____ relationship between alpha and beta, the most common way of reducing both Type 1 error and Type 2 error simultaneously is to _____ the sample size

Back 22

inverse (decreasing alpha leads to increase in beta)

Increase the sample size

Front 23

Procedure used when the mean of a normal distribution if not 0 and the standard deviation is not 1 in order to use the Standard normal tablet

Back 23

Z transformation, transformed value is known as z score, normal deviate, standard score, critical ratio

z = (raw score - mean)/standard deviation

Front 24

Number of observations that are free to vary after sample mean has been calculated, the number of observations less the number of restrictions place on them

Back 24

degrees of freedom (df) = n - 1

Front 25

Classifies objects into categories based on some defined characteristics. Then the number of objects in each category is counted (count # of observ with or without attribute), least precise, no logical order of the categories, categories are mutually exclusive

Back 25

Nominal Scale

Front 26

What type of measurement scale is religion?

Back 26

nominal scale

Front 27

What type of measurement scale is gender?

Back 27

Nominal Scale

Front 28

What type of measurement scale is eye color?

Back 28

Nominal Scale

Front 29

This measurement scale gives a logical order to classification. Differences in the amount of the measured characteristics are discernible and numbers are assigned according to that amount, categories are mutually exclusive

Back 29

Ordinal Scale

Front 30

What type of measurement scale is the letter-grading system (A,B,C,D,F)?

Back 30

Ordinal Scale

Front 31

Type of scale where the differences between levels of categories on any part of the scale reflect equal differences in the characteristic measured. The point 0 is just another point on the scale

Back 31

Interval Scale (Equal Unit Scale)

Front 32

What type of measurement scale is temperature?

Back 32

Interval Scale (Equal Unit Scale)

Front 33

The highest level in the hierarchy of measurement scales, most PRECISE measurement, a known/true zero reflects an absence of the characteristic measured

Back 33

Ratio Scale - allows us to make statements about the proportional amounts of the characteristic that two objects possess.

Front 34

This is an example of what type of scale, a bag of apples weighing 30 lbs does weigh twice as much as one weighing 15 lbs.

Back 34

Ratio Scale

Front 35

What is the hierarchy of measurement scales?

Back 35

Ratio (most precise)
Interval
Ordinal
Nominal

Front 36

These variables are measured on the nominal or ordinal scales, measurement consists of unordered or ordered (ranked) discrete categories

Back 36

Qualitative Variables
NO - nominal, ordinal

Front 37

These variables are measured on the interval or ratio scales

Back 37

Quantitative Variables

Front 38

Variables falling in a certain interval on which no theoretical restrictions are place. Measured along a scale

Back 38

Continuous

Front 39

These variables have no restriction place on them, there is no continuity

Back 39

Discrete

Front 40

These variables assume a value of one if a criterion is met, a value of zero otherwise

Back 40

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