fdt Flashcards

1
Q

is a tabular arrangement of data by categories and their corresponding frequencies.

A

Frequency distribution table

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2
Q

the data are incorporated in the text of the report.

A

Textual form

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3
Q

the data are presented in rows and columns.

A

Tabular form

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4
Q

utilized for an “easy to digest” information. This comes in graphs and diagrams.

A

graphics form

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5
Q

are data collected in an investigation and they are not organized systematically.

A

Raw data

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6
Q

-Raw data that are presented in the form of a frequency distribution.

A

Grouped data

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7
Q

2 METHODS OF ORGANIZING RAW DATA

A

Array and Stem-and-leaf display/diagram

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8
Q

An ordering of the observations from smallest to the largest or vice versa (low and high values can be easily perceived).

A

Array

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9
Q

gives a good overall impression of the data.

A

Stem and leaf

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10
Q

-Another way of presenting raw data is the
frequency table.
-When the data are arranged in tabular form by
the frequencies
-the arrangement itself is called

A

Frequency distribution

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11
Q

Statisticians

A

Freud and simon

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12
Q

Y =
X =
σ =
μ =
π =
e =

A

Y = height of the curve
X = any score in the distribution table
σ = standard deviation of the population
μ = mean of the population
π = 3.1416
e = 2.7183

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13
Q

z-Table also known as

A

the Table of Areas under the Normal Curve

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14
Q

e in statistics refers to the distribution of your data between the lowest and
highest values in the distribution.

A

range

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15
Q

is given by the midpoint of the upper limit of one class and the lower limit of the next
class

A

class boundary

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16
Q

The class boundary with a smaller value is referred to as the lower boundary

A

lower boudary

17
Q

The class boundary with a higher value is referred to as the upper boundary.

A

upper boundary

18
Q

is the average of the upper limit and the lower limit of a class in a frequency distribution.
In other words, the class mark is the mid-value of the given class interval.

A

class mark

19
Q

The values which determine the upper and lower limits of a class

A

class limits

20
Q

Smallest data value that can be included in the class

A

lower limit

21
Q

Largest data value that can be included in the class

A

upper limit

22
Q

is the number of values in a variable that is less than or equal to the value of certain variables. It equates to the total frequencies of the sum of the classes.

A

cumulative frequency

23
Q

refers to the difference of the upper-class limit and lower-class limit.

A

class interval

24
Q

refers to the difference between the upper and lower boundaries of a class in a frequency distribution.

A

class size

25
Q

Numbers that are used to describe set of data are called

A

DESCRIPTIVE MEASURES

26
Q

Another method of summarizing data is to compute numbers, such as average, that
describe a set of data.

A

measure of central tendecy

27
Q

is a single number that represents the typical score of the data.

A

A measure of central allocation or central tendency

28
Q

is the average value of all the data in the set.

A

mean

29
Q
  • is the value that has exactly half the data above it and half below it
A

median

30
Q

is the value that occurs most frequently on the set.

A

mode

31
Q

is defined as the sum of all the scores or data divided by the number of scores in the
data. In particular, the mean is denoted by x the scores

A

the mean for ungrouped data

32
Q

In general, the weighted mean of a group of numbers or scores designated by x1, x2, .., xn Which occur W1, W2, …, Wn respectively is

A

weighted arithmetic mean

33
Q

is average of a given set of data.

A

mean

34
Q

Is the sum of squares of differences between all numbers and means.

A

variance

35
Q

Square root of variance. It is a measure of the extent to which data varies from the mean

A

standard deviation

36
Q

m = Ex * P(x)
σ² = √(x -μ)² + P(x)
σ² = √E(x -μ)² + P(x)

A