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2. Descriptive Statistics
Descriptive statistics refer to methods for summarizing raw
observations into information that we can understand and share.
Inferential Statistics
Inferential statistics is a fancy name for methods that aid in
quantifying properties of the domain or population from a smaller set
of obtained observations called a sample.

4. Inferential Statistics
• Estimation
– e.g., Estimate the population
mean weight using the sample
mean weight
• Hypothesis testing
– e.g., Test the claim that the
population mean weight is 70 kg
Inference is the process of drawing conclusions or making decisions about a
population based on sample results

5. Descriptive Statistics
• Collect data
– e.g., Survey
• Present data
– e.g., Tables and graphs
• Summarize data
– e.g., Sample mean =
iX
n


6. Why study statistics?
1. Data are everywhere
2. Statistical techniques are used to make many decisions
that affect our lives
3. No matter what your career, you will make professional
decisions that involve data. An understanding of
statistical methods will help you make these decisions
efectively

7. Applications of statistical concepts
• Finance – correlation and regression, index
numbers, time series analysis
• Marketing – hypothesis testing, chi-square
tests, nonparametric statistics
• Personel – hypothesis testing, chi-square
tests, nonparametric tests
• Operating management – hypothesis
testing, estimation, analysis of variance,
time series analysis

8. Statistical data
 The collection of data that are relevant to the problem being studied
is commonly the most difficult, expensive, and time-consuming part
of the entire research project.
 Statistical data are usually obtained by counting or measuring items.
 Primary data are collected specifically for the analysis desired
 Secondary data have already been compiled and are available for
statistical analysis
 A variable is an item of interest that can take on many different
numerical values.
 A constant has a fixed numerical value.

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