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Biometrics > Exam 1 > Flashcards

Exam 1 Flashcards

1
Q

define population

A

everyone or everything that could be examined

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2
Q

example of population

A

an entire classroom of students

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3
Q

define sample

A

the individuals or things that are actually looked at

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4
Q

example of sample

A

a subset of students in the classroom that will be looked at

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5
Q

define experimental unit (EU)

A

one individual or thing you take a measurement on

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6
Q

example of an experimental unit

A

an individual in the classroom

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7
Q

define a variable

A

what is measure on each experimental unit

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8
Q

example of a variable

A

age

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9
Q

what is data value

A

one observation

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10
Q

example

A

a certain number of people at a certain age

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11
Q

what is data

A

all observations

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12
Q

example of data

A

list of ages of the entire group

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13
Q

define statistic

A

sample summary information (sample mean)

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14
Q

example of statistic

A

average age in sample size

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15
Q

define parameter

A

true population summary information (population mean)

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16
Q

example of parameter

A

average age of population

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17
Q

define descriptive statistics

A

information/ description about the subset of individuals examined

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18
Q

define inferential statistics

A

make inference to everyone using the description of the subset (taking descriptive statistics one step further)

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19
Q

define qualitative ordinal

A

a variable ordered with qualitative data; i.e. good, better, best

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20
Q

define quantitative discrete

A

a variable that uses whole numbers, i.e. # of people

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21
Q

define quantitative continuous

A

a number that is cut off to a certain number of decimal places, such as length, height, time, etc.

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22
Q

define qualitative nominal

A

a variable with a definitive name, or list; i.e. SSN or colors

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23
Q

what makes a ‘good’ sample

A

must be:

  • random: selected with some element of chance
  • represent entire population: everyone could have been sampled
  • must not have bias: bias has a direction in which some individuals have not been included in sample
  • independence: every EU is independent of other EUs
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24
Q

what is an experiment

A

a study in which a variable must be manipulated

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25
Q

what is a survey

A

a study in which data is simply collected from people

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26
Q
  1. Which of the following is not considered an aspect of a “good” sample?
    a. Random
    b. Represents entire population
    c. Large sample
    d. Independence
A

C. Large sample

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27
Q
  1. In an experiment to determine how the weight of a rat correlates to its likelihood of carrying a disease, what does the weight of an individual rat represent?
    a. Variable
    b. Experimental unit
    c. Data value
    d. Statistic
A

C. Data value

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28
Q

What is a judgment sample

A

a sample that can’t meet the four aspects of a ‘good’ sample

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29
Q

Which variable is a discrete quantitative variable?
A. The weight of all the students from University of Maryland
B. The number of siblings of the students in BIOM 301 course
C. The eyes’ color of students aged from 18-22 in Maryland
D. The phone number of the student’s parents

A

B. The number of siblings of the students in BIOM301 course

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30
Q 
WHICH ONE IS NOT A CHARACTER OF A GOOD SAMPLE
A.	RANDOM
B.	INDEPENDENT
C.	SPECIFIC 
D.	REPRESENTS ENTIRE POPULATION
A

C. specific

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31
Q

What are the two main areas of statistics?

A

descriptive statistics and inferential statistics

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32
Q

Does a big sample necessarily mean a good sample?

A

No.

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33
Q

is a small sample a bad sample?

A

no

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34
Q

1) Which of the following is NOT a qualitative summary graph?
a) Circle graph
b) Stem and Leaf plot
c) Bar graph

A

B. Stem and Leaf Plot

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35
Q

2) Which of the following is NOT one of the 4 measures of central tendency?
a) mean
b) mode
c) sample variance
d) midrange

A

C. Sample Variance

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36
Q

List the three indicative properties of a normal curve

A

always symmetrical, unimodal, and bell-shaped

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37
Q

What value is r when there is no linear relationship?

A

zero

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38
Q

what are 4 correlation terms?

A

linked, associated, connected, and tied to

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39
Q

Describe 3 reasons why r can equal zero.

A

r can equal zero when:

  • there is no relationship
  • y changes but x does not and vice versa
  • when the relationship is not linear
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40
Q

T/F correlation analysis is a method of obtaining the equation that represents the relationship between two variables

A

False; regression

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41
Q

t/f the linear correlation coefficient is used to determine the equation that represents the relationship between two variables

A

false, direction and tightness

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42
Q

t/f a correlation coefficient of positive or negative 1 means that the two variables are perfectly correlated

A

true

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43
Q

t/f whenever the slope of the regression line is zero, the correlation coefficient will also be zero

A

true

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44
Q

t/f when r is positive b(1) will be negative

A

false, positive

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45
Q

t/f the slope of the regression line represents the amount of change expected to take place in y when x increases by 1 unit

A

true

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46
Q

t/f correlation coefficients range between 0 and -1

A

false, -1 and +1

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47
Q

t/f the value being predicted is called the input variable

A

false, output variable

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48
Q

t/f the line of best fit is used to predict the average value of y that can be expected to occur at a given value of x

A

true

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49
Q

define bivariate data

A

data containing 2 observations for 1 experimental unit

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50
Q

correlation coefficient

A

statistical variable, r, representing a relationship’s direction and tightness in respect to linear correlation data. Value range from -1 to +1

51
Q

outlier

A

a datapoint that falls outside the range of bulk of the data set, can have a huge impact on statistical results

52
Q

covariance

A

when variables vary together in some relationship. E.g. both X and Y variables values move from low to high.
• if X increases and Y decreases, this is also a pattern of co-variance

53
Q

lurking variable

A

a third unmeasured variable that has a relationship to 2 variables and makes it appear that the measured variables are related to each other when actually they are related to the unmeasured variable.

54
Q

regression

A

generates a relationship that explains how Y changes as a function of X

55
Q

dependent or output variable

A

in terms of regression, the Y variable is the result of X (input variable)

56
Q

independent or input variable

A

in terms of regression, the X variable that results in a certain outcome or Y variable

57
Q

best fit line

A

a line in regression that minimizes the devation from data points to itself in the vertical direction

58
Q

intercept b0

A

the statistic in the line of best fit that describes the intercept value when x = 0

59
Q

slope b1

A

the statistic in the line of best fit that describes the direction of the relationship

60
Q

R^2

A

a value of regression- how much variability in y varaible is explained by x variable. Value ranges from 0-1

61
Q

prediction

A

a result of an observational or survey study analyzed using regression

62
Q

causation

A

a result of a controlled or experimental study analyzed with regression

63
Q

what graphs can be used to examine quantitative variables

A

box and whisker diagrams, stem and leaf diagrams and frequency histograms

64
Q

what graphs can be used to examine qualitative variables

A

circle graphs and bar graphs

65
Q

what must be present in a graph for it to be ‘good’

A
  • a title
  • labeled axes w/ units if available
  • a key if available
66
Q

is there a space in a bar graph of qualitative data

A

yes

67
Q

do frequency histograms have spaces between the bars?

A

no

68
Q

in grouped frequencies, what does n equal?

A

the sample size

69
Q

what is used to measure central tendency

A
  • mean
  • median
  • mode
  • midrange
70
Q

what is the mean

A

the average

71
Q

what is the median

A

the middle number

72
Q

what is the mode

A

the most frequent observation

73
Q

what is the midrange

A

the halfway point through the data (max + min)/2

74
Q

if a graph is symmetric and unimodal, are the mean, median, and midrange the same? the Mode?

A

yes, yes

75
Q

if a graph is symmetric and bimodal, are the mean, median, and midrange the same? the Mode?

A

yes, no

76
Q

what is the mean sensitive to?

A

outliers

77
Q

what is sample variance

A

avg squared difference in data set, in sq. units

78
Q

what is sample standard deviation

A

the square root of the sample variance

79
Q

in a density curve, the area under the curve represents what

A

100% of the data provided

80
Q

what is the rounding rule

A

when you calculate a statistic, take the answer 1 decimal place further than the original data

81
Q

what is a good way to hide the impact of a few large or small numbers? how can this be corrected?

A

use the mean to skew the results. report the median

82
Q

how can graphs be confusing

A
  • not being drawn to scale
  • using pictures or figures instead of bars
  • using 3-d graphs
  • misrepresentation
83
Q

does correlation mean causation

A

NO NO NO

84
Q

what variable can two seemingly correlated variables actually be correlated to?

A

a lurking variable instead of each other

85
Q

what are we asking for when we use a scatter plot

A

-is there a pattern?

how can we interpret that pattern?

86
Q

what two ways can we read scatter plots

A

correlation and regression

87
Q

what can r tell us?

A

the direction and tightness of the relationship between x and y

88
Q

in correlation, does flipping the axes influence r?

A

no

89
Q

what can affect r?

A

outliers

90
Q

what are some things to think about in regards to correlation

A
  1. flipping axes does not influence r
  2. changing one axis by a constant does not change r
  3. outliers can influence r
  4. lurking variables may be the cause of correlation
  5. be sure you have the full range
  6. do not draw conclusions outside of the range given
91
Q

what is the goal of linear regression

A

to generate a relationship that explains how Y changes as a function of X

92
Q

what does a best fit line do?

A

it minimizes deviations from data points to line in the VERTICAL DIRECTION

93
Q

what is b0

A

the intercept

94
Q

what is b1

A

the slope

95
Q

what is R^2

A

how much variability in the Y variable is explained by x variable, ranges from 0-1. represents tightness, but does not explain direction

96
Q

what explains direction in regression

A

the slope (b1)

97
Q

what is an experiement

A

a process that gives 1 result

98
Q

what is an outcome

A

all possible results

99
Q

what is an event

A

1 outcome of interest

100
Q

what is probability

A

the likelihood of an event

101
Q

what are three ways to find probability

A
  • theoretically
  • empirically
  • subjectively
102
Q

what is the rule of large numbers

A

with repetition, empirical results will approach the expected theoretical probability

103
Q

what 4 tools are given to think about probability

A
  • tree diagrams (cant directly calc. prob.)
  • venn diagrams (can)
  • contingency tables (can)
  • sample spaces (can)
104
Q

survey or experiment

A researcher watches 100 people purchase soda at a vending machine and recorded whether they chose regular or diet soda.

A

survey

105
Q

survey or experiment

Emergency room visitors complaining of stomach pain were randomly assigned to either a new drug treatment or a placebo.

A

experiment

106
Q

survey or experiment

A researcher compares the medical records for 100 people that live near high-power electric lines to 100 people that don’t live near such lines. Survey or Experiment

A

survey

107
Q

survey or experiment

. A researcher identified 20 students that got vigorous exercise at recess and then compared the grades of these students to a separate group of 20 who did not get vigorous exercise.

A

survey

108
Q

what is one thing the frequency histograms show that relative frequency histograms do not?

A

sample size

109
Q

The law of large numbers is used to calculate what?

A

emperical probability

110
Q

Parameter of sample size

A

N

111
Q

statistic of sample size

A

n

112
Q

parameter of mean

A

mu symbol

113
Q

statistic of mean

A

x (w/bar on top)

114
Q

parameter of standard deviation

A

sigma

115
Q

statistic of standard deviation

A

s

116
Q

list the 4 aspects of a good sample

A
  • random
  • independent
  • no bias
  • covers entire population
117
Q

T/F a normal curve is always unimodal

A

true

118
Q

if P(A) = P(A ̅) then the P (A) = 0.5

A

true

119
Q

t/f If two events are mutually exclusive, they are also independent

A

False

120
Q

a scatter diagram is an appropriate display of bivariate data when both variables are quantitative

A

true

121
Q

if the data points form a straight horizontal or vertical line, there is a strong correlation between the 2 variables.

A

False

122
Q

What of the following would not be appropriate when considering 2 qualitative variables

2 histograms
2 bar graphs
2 circle graphs

A

2 histograms

123
Q

T/F the value of the linear regression slope estimate will vary between -1 and +1

A

false

124
Q

t/f the data is the list of observations recorded for each of the experimental units in your study

A

true

Biometrics (3 decks)

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