Introduction to EDA Flashcards

1
Q

It is a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, and drawing conclusions based on the data.

A

STATISTICS

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2
Q

The practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample

A

STATISTICS

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3
Q

are methods for organizing and summarizing data.

A

Descriptive statistics

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4
Q

consists of procedures used to make inferences about population characteristics from information contained in a sample drawn from this population

A

INFERENTIAL STATISTICS

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5
Q

covers a large variety of techniques that allow us to make actual claims about a population based on sample of data

A

INFERENTIAL STATISTICS

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6
Q

The theory of statistics uses _________ to measure the uncertainty associated with an inference. It enables us to calculate the probabilities of observing specific samples under specific assumptions about the population. The statistician uses these probabilities to evaluate the uncertainties associated with sample inferences.

A

probability

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7
Q

information or facts necessary to conduct a certain study.

A

Data

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8
Q

in a statistical study is the group of objects drawn about which conclusions are to be drawn

A

POPULATION

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9
Q

is a subset of measurements selected from the population of interest

A

SAMPLE

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10
Q

A descriptive value for a population is called a

A

parameter

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11
Q

A descriptive value for a sample is called ________

A

statistic

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12
Q

measures a quality or characteristic on each experiment unit.

A

Qualitative data

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13
Q

measures a numerical quantity or amount on each experiment unit.

A

Quantitative data

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14
Q

Results from either a finite number of possible values or a countable number of possible values (that is, the number of possible values is 0, 1, 2, and so on)

A

Discrete data

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15
Q

Results from many possible values that can be associated with points on a continuous scale in such a way that there are no gaps or interruptions

A

Continuous data

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16
Q

To establish relationships between variables, researchers must observe the variables and record their observations This requires that the variables be _______

A

measured

17
Q

The process of measuring a variable requires a set of categories called a _______ and a process that classifies each individual into one category

A

scale of measurement

18
Q

is characterized by the data that consist of names, labels or categories only, and the data cannot be arranged in an ordering scheme

A

nominal level of measurement

19
Q

involves data that may be arranged in some order, but differences between data values either cannot be determined or are meaningless

A

ordinal level of measurement involves

20
Q

Is like the ordinal level, with the addition that meaningful amounts of differences between data can be determined. However, there is no inherent zero starting point.

A

Interval level measurement

21
Q

Is the interval level modified to include the inherent zero starting point. For values at this level, differences and ratios are meaningful.

A

ratio level of measurement

22
Q

A set of measurements that has not been organized numerically is called

A

raw data

23
Q

Data that are presented in the form of frequency distribution are called

A

grouped data

24
Q

The organization of raw data in table form with classes and frequencies An arrangement of a large mass of data by grouping into different classes of the same size and determining the number of observations that fall in each of the classes

A

Frequency Distribution

25
Q

data that can be placed in specific categories, such as gender, hair color or religious affiliation

A

Categorical Frequency Distribution

26
Q

A frequency distribution of numerical data The raw data is not grouped

A

Ungrouped Frequency Distribution

27
Q

A frequency distribution where several numbers are grouped into one class

A

Grouped Frequency Distribution

28
Q

categories (or classes) of scores, along with counts (or frequencies) of the number of scores that fall into each category

A

frequency table

29
Q

for a particular class is the number of original scores that fall into that class

A

frequency

30
Q

distribution represent data that can be placed in specific categories, such as gender, hair color or religious affiliation

A

Categorical frequency

31
Q

are the smallest number that can actually belong to the different classes

A

Lower class limits

32
Q

are the largest number that can actually belong to the different classes

A

Upper class limits are

33
Q

are the numbers used to separate classes, but without the gaps created by the class limits They are obtained increasing the upper class limits and decreasing the lower class limits by the same amount so that there are no gaps between consecutive classes The amount be added or subtracted is one half the difference between the upper limit of one class and the lower limit of the following class

A

Class boundaries

34
Q

are the midpoints of the classes. They can be found by adding lower class limits and dividing by 2.

A

Class marks

35
Q

is the difference between two consecutive lower class limits or two consecutive lower class boundaries.

A

Class width or Class size

36
Q

ratio of the class frequency to the total frequency

A

Relative Frequency

37
Q

if the frequencies are summed from bottom up The less than cumulative is constructed if the frequencies are summed from top down to find the number of observations less than a particular upper class boundary

A

Cumulative Frequency