Transcript Chapter 1 - University of Hawaii at Hilo

QBA 260
Chapter 1
Chapter 1 Topics
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Samples and Populations
Types of Data
Variables – Independent and Dependent
Probability
Hypothesis Testing
Types of Error
Intro to Excel
Samples and Populations
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Why do we sample?
Examples of sampling
What does “inferential statistics” mean?
Terms:
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Population – Parameters
Sample - Statistics
Types of Data
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Nominal
Ordinal
Interval
Ratio
Variables
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Variable = something that can take on more
than one value
Independent → Dependent
Examples
Probability
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Probability = the chance of something happening
Probability = (number of ways the event can
occur)/(total number of possible events)
What is the probability of getting a “head” if you
flip a coin?
What is the probability of getting 2 fours if you
roll two dice?
Conditional Probability – the chance of
something happening given some condition
Hypothesis Testing
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Null Hypothesis (H0) – our machine is
working correctly
Alternative Hypothesis (H1) – our machine is
not working correctly
Choices: to reject H0 or not to reject H0
Hypothesis Testing –
Another Example
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Let’s say there are 3 different teaching methods for a particular college
course:
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Full in-class
Full on-line
Combination of in-class and on-line
Null Hypothesis (H0) – Full in-class teaching is the best teaching method
Alternative Hypothesis (H1) – Full in-class teaching is not the best teaching
method
Choices: If you reject H0 then you know that full in-class teaching is not the
best method but you still do not know which of the other two methods is
better
Two types of Error
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Type 1 Error – when you reject H0 and you should
not have
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(example: you rejected the hypothesis that the machine was
working correctly and brought in the repair crew to fix it;
however, the machine was working correctly to begin with)
Type II Error – when you do not reject H0 and you
should have
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(example: you did not reject the null hypothesis and
assumed the machine was working correctly when it really
was not)
Chapter 1
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