³1username³2³2name³2text_default³2version³21³2ts³2982149038³2ip³2209.66.79.109³2data³2newauthor³31³3minor³30³3text³3:ProbabilityAndStatistics -- PlanningResearch -- InterpretingStatisticalData

[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3summary³3*³2tscreate³2982149038³2keepts³2982152535³2id³21272³2host³2cobrand.bomis.com³2revision³21³1username³2³2name³2text_default³2version³21³2ts³2982152535³2ip³2209.66.79.109³2data³2text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

1) How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of central tendancy''.

2) How do they differ? This is often called ''variability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''mean''', the '''median''', or the '''mode'''. 

The '''mean''' is what we call the ''average'' in ordinary English, just the sum of all the observations divided by the number of observations. Once we have chosen this method of describing the communality, we usually use the '''standard deviation''' to describe how the observations differ. The ''SD'' (as we abbreviate it) is the '''square root of the average of squared deviations from the mean'''.

The '''median''' is that value that separates the highest half of the sample from the lowest half. When we use the ''median'' to describe what the observations have in common, there are several choices for a measure of variability, the '''range''', the '''interquartile range''', and the '''absolute deviation'''. You can find out more about these from a good introductory statistics textbook.

[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3minor³30³3newauthor³30³3summary³3*³2tscreate³2982149038³2keepts³2982175727³2id³21272³2host³2cobrand.bomis.com³2revision³22³1username³2RoseParks³2name³2text_default³2version³21³2ts³2982175727³2ip³2209.66.79.109³2data³2newauthor³31³3minor³30³3text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

1) How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of central tendancy''.

2) How do they differ? This is often called ''variability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''mean''', the '''median''', or the '''mode'''. 

The '''mean''' is what we call the ''average'' in ordinary English, just the sum of all the observations divided by the number of observations. Once we have chosen this method of describing the communality, we usually use the '''standard deviation''' to describe how the observations differ. The ''SD'' (as we abbreviate it) is the '''square root of the average of squared deviations from the mean'''.

The '''median''' is that value that separates the highest half of the sample from the lowest half. When we use the ''median'' to describe what the observations have in common, there are several choices for a measure of variability, the '''range''', the '''interquartile range''', and the '''absolute deviation'''. You can find out more about these from a good introductory statistics textbook.

The '''mode''' is the value that has the largest number of observations. The '''mode'' is not necessarily unique, like the '''mean''' and the '''median'''.

[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3summary³3*³2tscreate³2982149038³2keepts³2982175833³2id³21015³2host³2cobrand.bomis.com³2revision³23³1username³2RoseParks³2name³2text_default³2version³21³2ts³2982175833³2ip³2209.66.79.109³2data³2text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

1) How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of central tendancy''.

2) How do they differ? This is often called ''variability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''mean''', the '''median''', or the '''mode'''. 

The '''mean''' is what we call the ''average'' in ordinary English, just the sum of all the observations divided by the number of observations. Once we have chosen this method of describing the communality, we usually use the '''standard deviation''' to describe how the observations differ. The ''SD'' (as we abbreviate it) is the '''square root of the average of squared deviations from the mean'''.

The '''median''' is that value that separates the highest half of the sample from the lowest half. When we use the ''median'' to describe what the observations have in common, there are several choices for a measure of variability, the '''range''', the '''interquartile range''', and the '''absolute deviation'''. You can find out more about these from a good introductory statistics textbook.

The '''mode''' is the value that has the largest number of observations. The '''mode''' is not necessarily unique, unlike the '''mean''' and the '''median'''.

[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3minor³30³3newauthor³30³3summary³3*³2tscreate³2982149038³2keepts³2982497078³2id³21015³2host³2cobrand.bomis.com³2revision³24³1username³2³2name³2text_default³2version³21³2ts³2982497078³2ip³2209.66.79.109³2data³2newauthor³31³3minor³30³3text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

1) How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of central tendancy''.

2) How do they differ? This is often called ''variability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''mean''', the '''median''', or the '''mode'''. 

The '''mean''' is what we call the ''average'' in ordinary English, just the sum of all the observations divided by the number of observations. Once we have chosen this method of describing the communality, we usually use the '''standard deviation''' to describe how the observations differ. The ''SD'' (as we abbreviate it) is the '''square root of the average of squared deviations from the mean'''.

The '''median''' is that value that separates the highest half of the sample from the lowest half. When we use the ''median'' to describe what the observations have in common, there are several choices for a measure of variability, the '''range''', the '''interquartile range''', and the '''absolute deviation'''. You can find out more about these from a good introductory statistics textbook.

The '''mode''' is the value that has the largest number of observations. The '''mode''' is not necessarily unique, unlike the '''mean''' and the '''median'''.
----
[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3summary³3*³2tscreate³2982149038³2keepts³2982497146³2id³2111³2host³2cobrand.bomis.com³2revision³25³1username³2³2name³2text_default³2version³21³2ts³2982497146³2ip³2209.66.79.109³2data³2text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

1) How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of CentralTendancy''.

2) How do they differ? This is often called ''variability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''mean''', the '''median''', or the '''mode'''. 

The '''mean''' is what we call the ''average'' in ordinary English, just the sum of all the observations divided by the number of observations. Once we have chosen this method of describing the communality, we usually use the '''standard deviation''' to describe how the observations differ. The ''SD'' (as we abbreviate it) is the '''square root of the average of squared deviations from the mean'''.

The '''median''' is that value that separates the highest half of the sample from the lowest half. When we use the ''median'' to describe what the observations have in common, there are several choices for a measure of variability, the '''range''', the '''interquartile range''', and the '''absolute deviation'''. You can find out more about these from a good introductory statistics textbook.

The '''mode''' is the value that has the largest number of observations. The '''mode''' is not necessarily unique, unlike the '''mean''' and the '''median'''.
----
[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3minor³30³3newauthor³30³3summary³3*³2tscreate³2982149038³2keepts³2982497279³2id³2111³2host³2cobrand.bomis.com³2revision³26³1username³2³2name³2text_default³2version³21³2ts³2982497279³2ip³2209.66.79.109³2data³2newauthor³30³3minor³30³3text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

1) How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of CentralTendancy''.

2) How do they differ? This is often called ''variability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''MeaN''', the '''MediaN''', or the '''MoDe'''. 

The '''mean''' is what we call the ''average'' in ordinary English, just the sum of all the observations divided by the number of observations. Once we have chosen this method of describing the communality, we usually use the '''standard deviation''' to describe how the observations differ. The ''SD'' (as we abbreviate it) is the '''square root of the average of squared deviations from the mean'''.

The '''median''' is that value that separates the highest half of the sample from the lowest half. When we use the ''median'' to describe what the observations have in common, there are several choices for a measure of variability, the '''range''', the '''interquartile range''', and the '''absolute deviation'''. You can find out more about these from a good introductory statistics textbook.

The '''mode''' is the value that has the largest number of observations. The '''mode''' is not necessarily unique, unlike the '''mean''' and the '''median'''.
----
[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3summary³3*³2tscreate³2982149038³2keepts³2982498184³2id³2111³2host³2cobrand.bomis.com³2revision³27³1username³2³2name³2text_default³2version³21³2ts³2982498184³2ip³2209.66.79.109³2data³2text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

#How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of CentralTendancy''.
#How do they differ? This is often called ''StatisticalVariability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''MeaN''', the '''MediaN''', or the '''MoDe'''. Sometimes, we choose specific values from the ''CumulativeDistributionFunction'' called '''QuanTiles'''.

The most common measures of variability for QuantitativeData are the VarianCe, its square root, the StandardDeviation, the RanGe, InterQuartileRange, and AbsoluteDeviation.

----
[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3minor³30³3newauthor³30³3summary³3*³2tscreate³2982149038³2keepts³2982498236³2id³2111³2host³2cobrand.bomis.com³2revision³28³1username³2³2name³2text_default³2version³21³2ts³2982498236³2ip³2209.66.79.109³2data³2newauthor³30³3minor³30³3text³3: ProbabilityAndStatistics -- StatisticalRegularity
: PlanningResearch -- InterpretingStatisticalData -- SummaryStatistics

In general, statistical data can be described as a list of ''subjects'' or ''Units'' and the data associated with each of them. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. 

We have two objectives for our summary:

#How do the data for different ''Units'' seem similar? Statistical textbooks call the answer to this question a ''measure of CentralTendancy''.
#How do they differ? This is often called ''StatisticalVariability''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the '''MeaN''', the '''MediaN''', or the '''MoDe'''. Sometimes, we choose specific values from the ''CumulativeDistributionFunction'' called '''QuanTiles'''.

The most common measures of variability for QuantitativeData are the VarianCe, its square root, the StandardDeviation, the RanGe, InterQuartileRange, and AbsoluteDeviation.

----
[http://netdial.caribe.net/~rabeldin/Home.html RABeldin ]
³3summary³3*³2tscreate³2982149038³2keepts³2982498508³2id³2111³2host³2cobrand.bomis.com³2revision³29