Exam 1 Flashcards

1
Q

What are the 4 methods of establishing truth?

A

Authority, Rationalism, Intuition, and Scientific Method

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2
Q

Authority

A

accepting information because it is from a highly respected source

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3
Q

Rationalism

A

acquisition of knowledge through reason or logic

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4
Q

Intuition

A

common-sense approach to acquiring knowledge; not based on reason

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5
Q

Scientific Method

A

relies on objective assessment

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6
Q

Observation vs Experimental

A

Observation does not influence any variable while experimental influences variables

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7
Q

Descriptive vs Inferential Statistics

A

Descriptive describes the data while inferential is used to make inferences (generalization)

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8
Q

Population

A

All the individuals of interest in a study

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9
Q

Sample

A

A set of individuals selected from a population

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10
Q

Variable

A

something that changes or has different values for different individuals

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11
Q

Independent Variable

A

is the variable that is manipulated

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12
Q

Dependent Variable

A

variable that is observed to asses the effect

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13
Q

Constant

A

value does not change; control

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14
Q

Data

A

measurement of observation of a variable

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15
Q

Statistic

A

a value that describes a sample

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16
Q

Parameter

A

value that describes a population

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17
Q

Why is random sampling important?

A

It allows the data to be representative of the population

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18
Q

What are the four measurement scales?

A

Nominal, Ordinal, Interval, and Ratio

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19
Q

Nominal

A

label and categorize, NO NUMBERS; think of brands

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20
Q

Ordinal

A

categorizes observations by ORDER; think of 1st place

21
Q

Interval

A

ordered categories, interval between categories of equal size; NO ZERO POINT (think of temperature)

22
Q

Ratio

A

same as interval but HAS A ZERO POINT (absolute zero); think of height

23
Q

Discrete Variable

A

whole countable numbers
Ex: 1, 2, 3, 4…

24
Q

Continuous Variable

A

infinite numbers possible
Ex: 1, 1.25, 1.26, 2, 2.34…

25
Q

Real limits

A

upper limit: will be .5 above the highest number
lower limit: .5 below the lowest number
EX: interval is 1-5 -> real limit is .5-5.5

26
Q

Rounding Numbers

A

below .5 = keep the same
above .5 = round up
equal to .5 (even) = stays the same
equal to .5 (odd) = round to next even number

27
Q

Frequency Distribution, why is it useful?

A

Present score values and their frequency of occurrence
shows the entire data

28
Q

Ungrouped vs. Grouped Frequency Distribution

A

ungrouped: raw scores can be pulled out, can find individual score
grouped: raw scores cannot be pulled out, no individual score, information is lost

29
Q

how to find the interval

A

i = range/ # of class interval
* class intervals are given*

30
Q

Relative Frequency (relative f)

A

proportion of total in interval
relative f = f/N
* should add up to 1*

31
Q

Cumulative Frequency

A

number of scores that fall bellow the upper real limit
* start at the bottom then add up
* final answer should equal to N

32
Q

Cumulative Percentage

A

Percentage of scores that fall below upper real limit of each interval
Cumulative % f= (f/N) x 100

33
Q

Percentile Point

A

% that falls bellow a specifice percentage (P30 = 30% of scores fall below this point)

34
Q

Percentile Point Formula

A

XsubL + (i/fsubi)(cumfsubp - cumfsubL)
XsubL = lower real limit of interval containing the percentile point
i = interval width
fsubi = freq. within the interval
cumfsubp = N x deciimal form of Psubx
cumfsubL = freq scores below the lower real limit (USE THE ROW BELOW)

35
Q

Percentile Rank

A

percentage of scores with values lower than the score in question
ex: 10% of scores fall below 59

36
Q

Percentile Rank Formula

A

(cumfsubL + (fsubi/i)(X-XsubL) / N) x 100

37
Q

Bar Graphs

A

best used for nominal or ordinal data
*bars do not touch

38
Q

Histogram

A

Best for interval or ratio data
* bars do touch each other

39
Q

Frequency Polygon

A

Used for interval or ratio data
* point is plotted over the midpoint of each interval

40
Q

Symmetrical vs Positive Skewed vs Negative Skewed

A

Symmetrical: normal curve
Positive: tail on the right
Negative: tail of the left

41
Q

Mean vs Median vs Mode

A

Mean: sum of all scores divided by total number
* is affected by outliers
Median: midpoint score
* not influenced by outliers
Mode: most common observation
* can be used for nominal data

42
Q

Overall Mean formula

A

M= sigmaX1 + sigmaX2 / n1 + n2
sigmaX1 = X-bar x n

43
Q

Mean and Median in Skewed Dist.

A

Positive = mean > median
Negative = mean < median

44
Q

Deviation Score

A

tells how far away the raw score is from the mean
sample: X - X-bar
Population: X - mu

45
Q

Sum of Squares (SS)

A

Raw Score method: sigmaXsqr - (sigmaX)sqr/N

46
Q

Variance calc. from SS

A

population: SS/N
sample: SS/N-1

47
Q

Standard Deviation calc. from SS

A

Population: sqrt SS/N or sqrt variance
Sample: sqrt SS/n-1 or sqrt variance

48
Q

Three measures of Variability

A

Range: max - min; overall spread
* is affected by extreme scores
Variance: average distance from the mean in squared units
Standard Deviation: average distance from the mean

49
Q

Z-Score

A

how many SD our score is from the mean