Statistics Chapt 1

Front 1

Statistics

Back 1

the scientific discipline that provides methods to help us make sense of data.

Front 2

steps in the Data analysis process

Back 2

1. Understand the nature of the problem - goal, ?s trying to answer
2. Deciding what to measure and how to measure it/ what info is needed to answer the ?s
3. Data collection - existing or new; careful plan
4. Data summarization and preliminary analysis - numerically and graphically
5. Formal data analysis - apply statistical methods
6. Interpretation of results

Front 3

3 critical tasks in Statistics

Back 3

1. collecting data
2. summarizing data
3. analyzing data

Front 4

Population of interest

Back 4

the entire collection of individuals about which info is desired

Front 5

Sample

Back 5

a subset of the population selected for study.

Front 6

Descriptive Statistics

Back 6

methods for organizing and summarizing data: tables, graphs, numerical summaries

Front 7

Inferential statistics

Back 7

generalizing from a sample to the population from which it was selected and assessing the reliability of such generalizations

Front 8

Variable

Back 8

any characteristic whose value may change from one individual to another.

Front 9

Data

Back 9

the result of making observations on one or more variables

Front 10

univariate data set

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data set consisting of observations on a single characteristic

Front 11

categorical/qualitative data

Back 11

identifies basic differentiating characteristics of the population

Front 12

bivariate data

Back 12

2 variables considered at the same time.

Front 13

2 types of data

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1) categorical 2) numerical

Front 14

2 types of numerical data

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1. discrete - each possible value corresponds to isolated points on a number line. COUNTING
2. continuous - the plausible set of values is an interval on the number line. MEASURING

Front 15

Frequency distribution - use

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Used for categorical data

a table that displays the possible categories along with the associated frequencies and/or relative frequencies

Front 16

Frequency

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the number of times the category appears in the data set

Front 17

relative frequency - how calculated

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the proportion of the observations that belong to that category.

= Frequency/ # of observations in the data set

Front 18

bar chart

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a graph of a frequency distribution of categorical data

Front 19

How to construct a bar chart

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- horizontal axis - category names
- vertical axis - frequency/relative frequency
- rectangular bar above each category that is the same width

Front 20

What to look for in a bar chart

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frequently and infrequently occurring categories

Front 21

When to use a dotplot

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with small numerical data sets

Front 22

how to construct a dotplot

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- horizontal line - mark with an appropriate measurement scale
- represent each value by a dot. Stack the dots vertically if a value has more than one observation.

Front 23

Dotplots convey info about:

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1) a representative or typical value
2) the extent to which the data values spread out
3) the nature of the distribution of values along the number line
4) the presence of unusual values