M2 Flashcards

1
Q

[ ] consists of organizing, summarizing, and visualizing data.

A

Descriptive Analytics

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2
Q

[ ] is the state of getting dispersed or spread.

A

Dispersion

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3
Q

[ ] means the extent to which numerical data is likely to vary about an average value.

A

Statistical Dispersion

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4
Q

[ ] helps to understand the distribution of data.

A

Dispersion

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5
Q

[ ] is the measure of variability, It is the average squared deviation from the mean.

A

Variance

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6
Q

[ ] is the measure how far the data deviates from the mean value. This is also know as the square root of variance.

A

Standard Deviation

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7
Q

[ ] is used to determine how estimations for a group of observations are spread out from the mean.

A

Standard Deviation

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8
Q

[ ] is the difference between the largest and the smallest value in the data.

A

Range

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9
Q

[ ] is the difference between the observed value of a data point and the expected value.

A

Deviation

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10
Q

[ ] is the average deviation of a data point from the mean, median, or mode of the data set.

A

Mean Deviation or Mean Absolute Deviation (MAD)

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11
Q

[ ] can be abbreviated as MAD.

A

Mean Deviation

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12
Q

[ ] describes the type of the graph.

A

Shape

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13
Q

Making a decision about the probability of data is based on [ ].

A

its shape

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14
Q

[ ] can be defined as a statistical measure that describes the lack of symmetry or asymmetry in the probability distribution of a dataset.

A

Skewness

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15
Q

Add a range of cells.

A

SUM(range)

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16
Q

Add cells from sum_range if the condition specified in criteria on range is met.

A

sumif(range, criteria, sum_range)

17
Q

Calculates the mean of a range of cells.

A

AVERAGE(range)

18
Q

Calculates the average_range if the condition in criteria on range is met.

A

AVERAGEIF(range, criteria, average_range)

19
Q

Calculates the media value for a data set: half the values in the dataset are greater than the median and half are less than the median.

A

MEDIAN(range)

20
Q

Returns the maximum value of a dataset.

A

MAX(range)

21
Q

Returns the minimum value of a dataset.

A

MIN(range)

22
Q

Returns the kth smallest or kth largest value in a specified data range.

A

SMALL(range, k) | LARGE(range, k)

23
Q

Counts the number of cells containing numbers in a range.

A

COUNT(range)

24
Q

Counts the number of non-blank cells within a range.

A

COUNTA(range)

25
Q

Counts the number of blank cells within a range.

A

COUNTBLANK(range)

26
Q

Counts the number of cells in range that are the same as value.

A

COUNTIF(range, value)

27
Q

Calculates the variance of a sample or an entire population; equivalent to the square of the standard deviation.

A

VAR(range) | VARP(range)

28
Q

Calculates the standard deviation of a sample or an entire population; the standard deviation is a measure how much values vary from the mean.

A

STDEV(range) | STDEVP(range)

29
Q

[ ] takes the average of a given set of data points over the past number of periods.

A

Moving Average

30
Q

Use [ ] to easily see the trends in the data.

A

moving average

31
Q

In a [ ], the length of the bars represent frequency of cost, and are arranges with longest bars on the left and the shortest on the right.

A

Pareto Chart

32
Q

[ ] is a methodology for monitoring a process to identify special causes of variation and signing the need for corrective action.

A

Statistical Process Control

33
Q

What are the two types of Statistical Process Control?

A
  • Common Cause Variation
  • Special Cause Variation
34
Q

[ ] is when process produce variations which can be considered natural or common to the process and will nearly always be present; the processes are in control.

A

Common Cause Variation

35
Q

[ ] is when processes display larger amounts of variation and often stem from external sources and are considered not in control.

A

Special Cause Variation