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Business Analytics > Chapter 3 > Flashcards

Chapter 3 Flashcards

1
Q

It is the practice or science of collecting and analyzing numerical data in large quantities especially for the purpose of inferring proportions in a hole from those in a representative sample

A

Statistics

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2
Q

It is used in almost all analysis in order to derive insights like projections and how different sets of data affect each other

A

Statistics

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3
Q

It is a central or typical value for a probability distribution

A

Measures of central tendency

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4
Q

It may also be called a center or location of the distribution

A

Measures of central tendency

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5
Q

Central tendency often called

A

Averages

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6
Q

Measures of central tendency

A

mean
median
mode

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7
Q

It can be calculated for either a finite set of values or for a theoretical distribution such as the normal distribution

A

Middle tendency

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8
Q

The tendency of quantitative data to cluster around some central value

A

Central tendency

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9
Q

It is the sum of all measurements divided by the number of observations

A

mean

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10
Q

An average of the data

A

Mean

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11
Q

It is the midpoint of our data that separates the upper and lower half of the data set

A

Median

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12
Q

These are the only measures of central tendency that can be used for ordinal data, in which values are ranked relative to each other but are not measured absolutely

A

Median and mode

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13
Q

The most frequent value in the data set

A

Mode

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14
Q

The only central tendency measure that can be used with nominal data which have purely qualitative category assignments

A

mode

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15
Q

Also called the variability, scatter, spread

A

Measures of dispersion

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16
Q

It is the extent to which a distribution is stretch or squeezed

A

Dispersion

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17
Q

Measures of dispersion

A

range
mad
variance
standard deviation

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18
Q

The difference between the smallest and largest data point in the set

A

range

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19
Q

It is the average of the absolute deviations from a central point

A

Mean absolute deviation

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20
Q

It is a summary statistic of statistical dispersion or variability

A

Mean absolute deviation

21
Q

In simpler terms it means how far are the data points from the mean

A

Mean absolute deviation

22
Q

This is another way of measuring the spread between numbers in a data set

A

Variance

23
Q

It measures how far its number in the set is from the mean

A

Variance

24
Q

It is simply the square root of the variance

A

Standard deviation

25
Q

It is the most commonly used measure to express dispersion

A

Standard deviation

26
Q

Are cut points dividing the range of a probability distribution into continuous intervals with equal probability or dividing the observations in a sample in the same way

A

Quantiles

27
Q

Quantiles

A

quartiles
deciles
percentiles

28
Q

Divide or cut the data into four parts

A

Quartiles

29
Q

Are often used as a measure of spread of the data in what is called interquartile range (IQR)

A

Quartiles

30
Q

The difference between the third quartile and the first quartile

A

Interquartile range

31
Q

Is the median of the first half of the data set and marks the point at which 25% of the data values are lower and 75% are higher

A

First quartile

32
Q

Is the median of the second half of the data set and marks the point at which 25% of the data values are higher and 75% lower

A

Third quartile

33
Q

cut into 10

A

deciles

34
Q

divide into 1% segments

A

percentiles

35
Q

are used for larger data sets

A

deciles and percentiles

36
Q

It is a way of standardizing scores on the same scale by dividing a scores deviation by the standard deviation in a data set

A

Standard score (z-score)

37
Q

It measures the number of standard deviations a given data point is from the mean

A

Standard score

38
Q

What it means if it is a negative z score

A

value is less than the mean

39
Q

What it means if it is a positive z score

A

value is greater than the mean

40
Q

It represents the ratio of the standard deviation to the mean and it is a useful statistic for comparing the degree of variation from one data series to another even if the means are drastically different from one another

A

Coefficient of variation

41
Q

It allows investor to determine how much volatility or risk is assumed in comparison to the amount of return expected from investments

A

Coefficient of variation

42
Q

Refers to distortion or a symmetry in a symmetrical bell curve or normal distribution in a set of data

A

Skewness

43
Q

What it means if it is a positive skew

A

The mean is greater than the median

44
Q

What it means if it is a negative skew

A

The mean is less than the median

45
Q

It is a statistical measure that expresses the extent to which two variables are linearly related

A

Correlation

46
Q

It is a common tool for describing simple relationships without making a statement about cause and effect

A

Correlation

47
Q

Correlation coefficient of positive one indicates a

A

perfect positive correlation or direct relationship

48
Q

Correlation coefficient of negative 1 indicates a

A

Perfect negative correlation or inverse relationships

49
Q

Correlation coefficient near zero indicates a

A

No correlation

Business Analytics (4 decks)

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