2: Displaying and Exploring Data; Sampling Methods and Central Limit Theorem Flashcards

1
Q

A ___ summarizes the distribution of one variable by stacking dots at points on a number line that shows all values of the variable; identical observations are stacked.; most useful in smaller data sets.

A

Dot plot

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2
Q

A ___ is a method used to display a variable distribution using every value; classified by data’s leading digit.

A

Stem-and-leaf display

Stem: the leading digit or digits
Leaf: the trailing digits

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3
Q

___ are values of an ordered data set (small to large) that divide the data into four intervals.

A

Quartiles

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4
Q

___ are values of an ordered data set (small to large) that divide the data into 10 equal parts.

A

Deciles

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5
Q

___ are values of an ordered data set (small to large) that divide the data into 100 intervals.

A

Percentiles

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6
Q

___ is the most widely used measure of dispersion.

A

Standard deviation

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7
Q

___ is a graphical display that shows the general shape of a variable’s distribution; based upon five statistics: the minimum value, the first and third quartile, and the maximum value.

A

Box plots

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8
Q

An ___ is a value on a box plot that is inconsistent with the rest of the data. It is defined as a value that is more than 1.5 times the interquartile range smaller than Q1 or larger than Q3.

A

Outlier

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9
Q

There are four shapes commonly observed:

  1. ___
  2. ___
  3. ___
  4. ___
A
  1. Symmetric
  2. Positively skewed
  3. Negatively skewed
  4. Bimodal
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10
Q

In a ___ distribution the mean and median are equal and the data values are evenly spread around these values. The shape of the distribution below the mean and median is a mirror image of distribution above the mean and median.

A

Symmetric

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11
Q

A distribution of values is ___ if there is a single peak, but the values extend much farther to the right of the peak than to the left of the peak; the mean is larger than the median.

A

Positively skewed or skewed to the right

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12
Q

In a ___ distribution there is a single peak, but the observations extend farther to the left, in the negative direction, than to the right; the mean is smaller than the median.

A

Negatively skewed

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13
Q

A ___ distribution will have two or more peaks; when the values are from two or more populations.

A

Bimodal

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14
Q

A ___ is a graph in which the values of two variables (X and Y) are plotted along two axes, the pattern of the resulting points revealing any correlation present; required to be at least interval scale.

A

Scatter diagram

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15
Q

A ___ is a table used to classify observations according to two identifiable characteristics.

A

Contingency table

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16
Q

What are the 5 reasons to sample?

  1. ___
  2. ___
  3. ___
  4. ___
  5. ___
A
  1. To contact the whole population would be time-consuming
  2. The cost of studying all the items in a population may be prohibitive
  3. The physical impossibility of checking all items in the population
  4. The destructive nature of some tests
  5. The sample results are adequate
17
Q

A ___ is a sample selected so that each item or person in the population has the same chance of being included.
I.e., name in a hat OR a table of random numbers (not always effective)

A

Simple random sample

18
Q

___ is when a random starting point is selected, and then every k’th member of the population is selected (can be biased)

A

Systematic random sampling

19
Q

A ___ occurs when a population is divided into subgroups, called strata, and a sample is randomly selected from each stratum.
I.e., college students can be grouped as full time or part time; male or female; freshman, sophomore, junior, or senior.

A

Stratified random sample

20
Q

When a population can be divided into groups based on some characteristic; the group is called ___.

21
Q

___ occurs when a population is divided into groups using naturally occurring geographic or other boundaries. Then, are randomly selected and a sample is collected from each group; often employed to reduce the cost of sampling a population scattered over a large geographic area.

A

Cluster sampling

22
Q

___ is the difference between a sample statistic and its corresponding population parameter.

A

Sampling error

23
Q

The ___ is a probability distribution of all possible sample means of a given sample size.

A

Sampling distribution of the sample mean

24
Q

The ___ theorem states that, for large random samples, the shape of the sampling distribution of the sample mean is close to the normal probability distribution; this theorem is true for all population distributions.

A

Central limit theorem

25
The sampling distribution will be normally distributed under two conditions: 1. ___ 2. ___
1. When the samples are taken from populations known to follow the normal distribution. 2. When the shape of the population distribution is not known, sample size is important.
26
The ___ will be exactly equal to the population mean if we are able to select all possible samples of the same size from a given population
Mean of the distribution of sample means μ=μx
27
There will be less dispersion in the sampling distribution of the sample mean than in the___.
Population
28
___ destroys a sample in the course of measuring it. | I.e., breaking a table to determine weight capacity
Destructive Testing