Statistics Frequency Distribution And Population

Chapter 1-4 Statistics Frequency Distribution And Population

In this chapter we discuss statistics frequency distribution and population.


Population

the entire collection of individuals or objects about which information is desired. may be considered to be finite or infinite


Census

a collection of data from every member of the population


Sample

a sub-collection or subset of a population selected for study


Parameter

a numerical characteristic of a population


Statistic

a numerical characteristic of a sample


Variable

the characteristic about which we are interested


Data

the observations that have been collected


Qualitative Data

categorical or attribute data


Quantitative Data

numerical data


Discrete Data

count dataquantitative)


Continuous Data

measure dataquantitative)


Sampling Error

the difference between the result of a sample and the result for the entire population. caused by random fluctuations of the sample- i.e. by chance


Normal

bell-shaped distribution


Statistically Significant

observation that is extremely unlikely to happen simply by chance


Descriptive Statistics

the collection, presentation, and description of data


Inferential Statistics

interpreting the data in order to draw conclusions about the population, based on information obtained from a sample


Frequency Distribution

a chart or table giving the values of a variable together with their corresponding frequencies


Blood Type

example of a frequency distribution for qualitative data


Class Width

the difference between two consecutive lower class boundaries


Class Midpoints

the center value of each class


Relative Frequency

a proportional measure of frequency, calculated by dividing the frequency of that class by the total frequency of the data set


Pie Chart

a circular graph showing the relationships of parts to a whole, only one variable at a time may be displayed


Bar Graph

a rectangular graph representing quantities using heights of detached rectangles, generally used to display qualitative or discrete data, displays an ungrouped frequency distribution


Histogram

a rectangular graph representing quantities using heights of attached rectangles, used to display continuous data, displays a grouped frequency


Elements of a Histogram

a title, a horizontal scaleidentifying the variable), a vertical scaleidentifying frequencies)


Stem and Leaf Display

combines graphing and sorting the data, split into the leading digits, the trailing digits


Outlier

an unusually large or small data value with respect to its data set


Dotplot

a number line above which each data value is plotted as a point


Measures of Central Tendency

the middle or center of a data set, averages- mean, median, mode, midrange


Averages

mean, median, mode, midrange


Arithmetic Mean

adding the data values and dividing by the number of data values, balance point of a data set


X Bar

sample mean – statistic


Mu

population mean – parameter


Median

physical center of a data set


Mode

the most frequently occurring value in a data set


Bimodal

when two values occur with the same greatest frequency


Midrange

the value midway between the lowest and highest values in a data set, L+H/2


Measures of Dispersion

measure the spread or variability of the data set


Range

the difference between the largest and smallest values in a data set


Standard Deviation

the average distance of the data values from their mean


Within 1 Standard Deviation

68%


Within 2 Standard Deviations

95%


Within 3 Standard Deviations

99.7%


Measures of Relative Standing

indicates the position of a data value in terms of its data set


Z-Score

gives the position of a data value in terms of standard deviations from its mean


Quartiles

divide an ordered data set into four equal parts


Five-Number Summary

Lowmin), Q1, medianQ2), Q3, and highmax)


Interquartile Range

Q3-Q1


Probability

______ that an event will occur is the relative frequency with which that event can be expected to occur


P

theoretical probability


P’

empirical probability


Sample Space

the set of all possible outcomes of an experiment


Sample Points

the individual outcomes in a sample space


Event

any subset of a sample space


A Complement

the set of all sample points in the sample space that do not belong to A


Compound Event

any event made up of two or more sample events


P(A or B)

probability that either A or B occurs


Mutually Exclusive

events cannot happen at the same time


General Addition Rule

P(A or B) = P(A) + P(B) – P(A and B)


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