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# Statistics Introduction Chapter 1

## Terms

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What is descriptive statistics?
The use of graphs, charts and tables and the calculation of various statistical measures to organize and summarize information.
Population
The complete collection of individuals, items, or data under consideration in a statistical study.
Sample
The protion of the populaiton selected for analyais.
Inferential Statistics
Consists of techniques for reaching conclusions about a populaiton based upon information contained in a sample.
Variable
A characteristic of interest concerning the individual elements of a population or of a sample.
Observation
A particular element from the sample or population.
Data Set
The observations of a variable for the elements of the sample.
Quanititative Variable
when the decription of the variable results in a numerical number. ( It would be necessary to perform a count)
Discrete Variable
A quantitative variable whose values are countable. They usually result "from counting".
Continuous Variable
is a quanitifyable variable that can assume any numerical value over an interval or over several intervals. It ususally results from making a measurmennt of some type.
Qualitative
determined when the description of the charasteristic of interest results in a nonnumerical value. Maybe classified into two or more categories.
Nominal scale
data that areused for category identification. Type of measurement- characterised by names, labels or categories.* can not be used in an ordering scheme. Arithmetic operations are not performed for nominal data.
Ordinal scale
data that can be set in some type of order.
What are the key features of a "Oridinal Level of Measurement"?
1. data that applies to categories that can be ranked. 2. data can be arranged in an ordering scheme.
What are the key fetures of the "Nominal Scale"?
1. Differences between the data values can not be determined and are meaningless.
interval scale
data that can be arranged in some order and for which differences in data values are meaningful.
What is the key feature of " interval level of measurment"?
1. results from counting or measuring.
What is the key feature of interval scale data?
the data can be arranged in an ordering scheme and the differences can be calculated and interpreted.
Expalin what how the value of zero is used when using interval data.
It is arbitrarily choosen and does not imply an absence of the characteristic being measured.
Are ratio's meaningingful for interval data?
No.
What is an example of "interva data?"
1)The Standfor-Binet IQ Scores. IQ scores can be arrange in order. Differences can be calculated and interpreted.An IQ score of zero does not indicate a lack of intelligence.
Name another example of "interval level data".
Temperatures. Temperatures can be arranged in order.Differences maybe calculated and interpreted.Ratio's are not readily interpretable. A temp of 0 does not indicate a absence of warmth.
Is a test score an example of " interval level data?"
Yes. Test scores can be arranged in order.Differences maybe calculated and interpreted.Ratio's are not readily interpretable. A test of 0 does not indicate a absence of knowledge.
What is a "ratio scale"?
Applied to data that can be ranked, and all arithmeitc operationsincluding division can be performed.
Is division by "0" excluded in a "ratio scale?"
Yes
What are the key features of "ratio scale data?"
1. Can be arranged in an ordering scheme. 2.Differences and rations can be calculated and interpreted. 3. Ratio level data has an absolute zero, a value of zero indicates a complete absence of the characteristic of interest..
What doe "Σx" mean?
Sigma. The sum of all scores of x
What is "raw data"?
information obtained by observing values of a variable.
What are the main features of a frequency distribtuion for qualitative data.
1. lists all categories and the number of elements that belong to each of the categories.
What are the steps to finding " relative frequency"?
divide the frequency of a category by the frquency of all categories.
What will the sum of all the relative frequencies be equal to?
One
How do you find the percentage for a category?
Multiply the relative frequency for the category by 100. ( The sum of the percentage for all categories will always equal 100%.
Where are the categories placed on a bar graph?
On the horizontal axis.
Where are the frquencies marked on a bar graph?
on the vertical axis.
What type of data is a pie chart used to graph?
Qualitative data.
What is a historgram?
It is a graph that displays the classes on the horizontal axis and the frequencies of the classes on the verticle axis.
How is a histogram different than a bar graph?
A histogram utilizes classes or intervals while a bar graph utilizes categories and frequencies.
What is the "cumulitive realtive frequency"?
It gives the total number of values that fall below variuos class boundaries of a frequency distribution.
How is a culmulative relative frequency obtained?
It is obtained by dividing a cumulative frequency by the total nubmer of observations in the data set.
How is the Cumulative Percentage obtained?
1. By multiplying cumulative relative frequencies by 100.
What are the most common measures of centeral tendency?
mean, median & mode
What is the difference between raw (ungrouped data) and grouped data?
Data that is presented in the form of frequency distribution is grouped, ungrouped data is just a list of data
How do you figure out the mean?
Devide the total scores by the number of scores observed.

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