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RESEARCH > research lecture 4 > Flashcards

research lecture 4 Flashcards

1
Q

what are methods for organizing and summarizing data

A

descriptive statistics

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2
Q

what is a descriptive value for a population called

A

parameter

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3
Q

what is a descriptive value for a sample called

A

statistic

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4
Q

what is the first task for a researcher after collecting the data

A

organize and simplify the data to get a general overview of the results

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5
Q

one method for simplifying and organizing data is to construct a

A

frequency distribution

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6
Q

what presents an organized picture of the entire set of scores, and it shows where each individual is located relative to others in the distribution.

A

frequency distribution

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7
Q

what is used when a set of scores covers a wide range of values.

A

Grouped frequency distribution

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8
Q

Grouped frequency distribution and frequency destruction are frequently displayed as what

A

histograms

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9
Q

If the scores in the population are measured on an interval or ratio scale and the N is large, it is customary to present the distribution as a

A

smooth curve

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10
Q

the smooth curve emphasizes the fact that the distribution is not showing what

A

the exact frequency for each category

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11
Q

how would you like the shape of your data to be

A

symmetrical

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12
Q

what shape is when the two sides are close to mirror images of each other…

A

symmetrical

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13
Q

what shape is when scores pile up on one side of the distribution, leaving a “tail” of a few extreme values on the other side.

A

skewed

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14
Q

scores bunched at low values with the tail pointing to high values ais called what kind of frequency distribution

A

positive skew

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15
Q

scores bunched at high values with the tail pointing to low values is called what kind of frequency distribution

A

negative skew

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16
Q

what kind of kurtosis is frequency distribution is a higher/ thinner peak

A

leptokurtic

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17
Q

what kind of kurtis is frequency distribution is a lower/ broader peak

A

platykurtic

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18
Q

which kurtosis frequency distribution is hard to get significance and has increase variability

A

platykurtic

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19
Q

which kurtosis frequency distribution has better significance and doesn’t have a high variability

A

leptokurtic

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20
Q

what is a statistical measure that describes the center of the distribution and represents the entire distribution of scores as a single number.

A

central tendency

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21
Q

what are the 3 commonly used techniques from measuring central tendency

A

the mode , median and mean

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22
Q

which central tendency is the most frequent score

A

mode

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23
Q

which central tendency is have 2 modes called anf having several modes

A

bimodal and multimodal

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24
Q

what is defined as the most frequently occurring category or score in the distribution.

A

the mode

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25
Q

what is the mode appropriate for

A

nominal, ordinal, interval, or ratio level data.

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26
Q

if teh score in a distribution are listed in order form smallest to largest , what is defined as the midpoint of the list

A

the median

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27
Q

what is the median appropriate for

A

ordinal, interval, or ratio level data.

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28
Q

what is one advantage of the median

A

that it is relatively unaffected by extreme scores

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29
Q

what is a con for the median

A

doesn’t tell u the significant difference

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30
Q

what is the most commonly used measure of central tendency.

A

the mean

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31
Q

Computation of the mean requires scores that are numerical values measured on an…

A

interval/ratio scale

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32
Q

when a distribution contains a few extreme scores (skewed) the mean will be pulled toward the ___

A

extremes

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33
Q

when do you not report the mean

A

with data from a nominal score or ordinal scale

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34
Q

Because the mean, the median, and the mode are all measuring central tendency, the three measures are often ___ related to each other.

A

systematically

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35
Q

in a symmetrical distribution what will always be equal

A

mean and median

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36
Q

in a skewed distribution where will each central tendency be (mean , median and mode)

A

the mode will be located at the peak
mean is usually closer to the tail
median is in between the mean and mode

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37
Q

what serves both as a descriptive measure and as an important component of most inferential statistics

A

variability

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38
Q

what is it called when variability measures the degree to which the scores are spread out or clustered together in a distribution.

A

descriptive statistic

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39
Q

what is it called when variability provides a measure of how accurately any individual score or sample represents the entire population.

A

inferential statistics

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40
Q

what does less variability mean

A

better representation

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41
Q

what is the difference when the population variability is small and large

A

When the population variability is small, all of the scores are clustered close together and any individual score or sample will likely provide a good representation of the entire set.
On the other hand, when variability is large and scores are widely spread, it is easy for one or two extreme scores to give a distorted picture of the general population.

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42
Q

what are the 2 ways that variability can be measure with

A

the range and SD/ variance

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43
Q

variability is determined by measuring the ___

A

distance

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44
Q

what is the total distance covered by the distribution, from the highest score to the lowest score.

A

the range

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45
Q

For the data set: 2, 5, 7, 9, 10….the range is

A

10-2 or 8

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46
Q

what measures the standard (average) distance between a score and the mean.

A

standard deviation

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47
Q

what kind of significance does a large standard deviation have

A

none

48
Q

what kind fo significance does a small standard deviation have

A

some sig

49
Q

why does a large SD have a decreased significance

A

increase variability
decreased number of participants
decreased difference in means

50
Q

if you want to increased significance what can you do

A
  1. decreased variability but decreased SD and variance
  2. increased the number of participants
  3. increased the difference of means
51
Q

what percent of of the scores will be within 1 +/- standard deviation of the mean for a normal distribution

A

70%

52
Q

what percent of of the scores will be within 2 +/- standard deviation of the mean for a normal distribution

A

95%

53
Q

what percent of of the scores will be within 3 +/- standard deviation of the mean for a normal distribution

A

99%

54
Q

what does the z score tell you

A

exactly where the score is located relative to all the other score

55
Q

if the z score is positive what does that mean ? negative ?

A

if it is postivie that mean X value is located about the mean and if it is negative then the X value is located below the mean

56
Q

The numerical value of the ____ corresponds to the number of standard deviations between X and the mean of the distribution.

A

z score

57
Q

a score that is located 2 standard deviations above the mean will have a z score of what

A

+2.00

58
Q

what z score always indictes a location above the mean by 2 standard deviations

A

z score for +2.00

59
Q

when you change the population score to the population of z scores on the graph does the graph change

A

no

60
Q

what is the formula for computing the z score for any value of x

A

z= X (your score) - the mean / standard deviation

61
Q

You scored a 82 on a test with a mean score of 70 and a standard deviation of 12. Your z-score will be

A

1+ bc the standard deviation is 12 and the mean is 70 and you scored a 82 which is 12 above 70 which is the SD so u go up 1 SD from the mean

62
Q

You scored a 70 on a test with a mean score of 70. Your z-score is

A

0

63
Q

The fact that z-scores identify exact locations within a distribution means that z-scores can be used as what 2 statistics

A

descriptive statistics and as inferential statistics.

64
Q

what statistics does the , z-scores describe exactly where each individual is located.

A

descriptive

65
Q

what statisitcs does the z-scores determine whether a specific sample is representative of its population, or is extreme and unrepresentative

A

inferential

66
Q

what is the advantage of standardizing distributions

A

that 2 or more different distributions can be compared

67
Q

N=60, Mean=83, Standard Deviation=10, what is the Z-score for 83?

A

0

68
Q

N=32, Mean=120, Standard Deviation=23, what is the Z-score for 143?

A

+1

69
Q

• N=1000, Mean=100, Standard Deviation=8, what is the Z-score for 92?

A

-1

70
Q

N=50, Mean=50, Standard Deviation=10, what value has a Z-Score of -2

A

30

71
Q

what are methods for using sample data to make general conclusions (inferences) about populations.

A

inferential statistics

72
Q

for inferential statistics what does the research begin with and what does the actual research do

A

begins with a question about a population and the actual research is conducted using a sample

73
Q

Rather than just describing the sample data (descriptive statistics)…inferential statistics use the sample to do what

A

infer something about the population in terms of probability

74
Q

When a set of scores is represented by a frequency distribution and that distribution is similar to a normal distribution, probabilities can be defined by

A

proportions of the distributions

75
Q

Probability =

A

Proportion

76
Q

When graphed, probability can be defined as what

A

the proportional area under the curve.

77
Q

Drawing a vertical line through a normal distribution divides the distribution into two sections what is the larger section called and what is the smaller sections called

A

larger section is called the body and the smaller section is called the tail

78
Q

what will give you ALL POSSIBLE proportions/probability for every z score.

A

the unit normal table

79
Q

so if you know the z score what can u look up ?

A

proportion/ probability

80
Q

if you know the proportion/probability what can you look up

A

z score

81
Q

if the z score is 1.96 how much of the area is in the tail

A

2.5%

82
Q

If we think if the area in the tails when we use 1.96 (to the right)…and -1.96 (to the left)…there would be a total of ___ % in the 2 tails.

A

5

83
Q

Do we use the normal distribution when running statistical tests

A

no

84
Q

what theory is as the sample size increases it approaches a normal distribution.

A

central limit theorem

85
Q

the smaller the sample size the smaller the ___ will be on the graph

A

tail

86
Q

Population data can be ANY size and shape….but thanks to the central limit theorem…

A

single sample of 30+ it will be very close to a normal distribution

87
Q

N>30 is only ___ assumption for parametric testing

A

1

88
Q

A sample size of ___ is often used as a rule of thumb for statistics since the sample of scores will be approximately normal.

A

30

89
Q

what software do we use for a better estimate of the number or participants needed for a study

A

g power

90
Q

If we are comparing more than two groups or time periods, or we have a factorial research design (2+IV) we run a statistical test called and what distribution does it use

A

ANOVA and it uses the F distribution

91
Q

if we are comparing 2 groups or two time period we run which test ad what distribution does it use

A

t test and uses t distribution

92
Q

if we are comparing the portions of people in different groups we use which distribution

A

the chi square

93
Q

what test compares observed frequencies to what would be considered the expected frequencies

A

chi square

94
Q

what is a value that describes the difference between the sample mean and the true population

A

standard error of the mean

95
Q

what measure the amount of variability or dispersion for a set of data from the mean ?

A

SD

96
Q

what measures how far the sample mean of the data is kiley’s to be from the true population mean

A

standard error of the mean

97
Q

is the standee error of the mean smaller or larger then the SD

A

always smaller

98
Q

a small standard error of the meal is interpreted as what

A

less sampling error

99
Q

as the sample size increased what happens to the standard error of mean if the SD stays the same

A

it decreased

100
Q

what is the equation for standard error of the mean

A

SD / square root of N (sample size)

101
Q

most researchers will report what estimation

A

point estimation and interval

102
Q

what estimation is a mean of your sample

A

point

103
Q

what estimation is a span of number values that incorpates the mean

A

interval mean

104
Q

what estimation is the sample mean…and it is used to estimate the population me

A

point

105
Q

My sample of entering DPT students has an undergraduate GPA of 3.4 (95%CI: 3.2-3.6), so I will assume that the population of all DPT students has a GPA of 3.4.. what foes the CI mean

A

I am 95% confident that the real population mean is between 3.2 and 3.6.

106
Q

what is a range of numbers inferred from the sample that has a known probability of capturing the true population parameter over the long run (ex/ over repeated sampling).

A

interval estimate AKA a confidence interval

107
Q

The “beauty” of adding confidence intervals to your results is that the reader knows the probability that what

A

the true mean has been reported

108
Q

Functional Outcomes in those with CVA and TBI after residential inpatient care at NeuroRestorative in Houston

Is this a prospective study?
Is this a 1b level study?
Is this a truly experimental study?
Could this study be reviewed using a PEDro scale?

A

yes and the. no 3x

109
Q

If the calculated t-score is greater than our calculated t-value…it’s ____ . (2-tail)

A

significant

110
Q

which sample mean is more likely to closer to the population mean?

A

which ever sample mean is closer to the actual mean

111
Q

in box plots what does the box show

A

the median
the upper and lower quartile (25% and 75%)
the limits within which t middle 50% of scores lie

112
Q

in box plots what does the box show

A

the median
the upper and lower quartile (25% and 75%)
the limits within which t middle 50% of scores lie

113
Q

in a box plot what does the whiskers show u

A

the range of scores
th eli it’s within which the top and bottom 25% of the scores lie

114
Q

in the error bar charts the bar usually showwhat score

A

the mean

115
Q

in the error bar charts the bar usually showwhat score

A

the mean

116
Q

The error bar displays the precision of the mean in one of three ways:

A

› The confidence interval (usually 95%)
› The standard deviation
› The standard error of the mean (SEM)

117
Q

no

A

RESEARCH (11 decks)

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