Download or “reject” the null hypothesis?

Name:________________________________________________
ESR Notes
EXPERIMENTAL DESIGN TERMS
TITLE - The title should describe & include the IV & DV
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“The Effect of Surface Type on Heat Absorption.”
“The Correlation between a Galaxy’s Distance from Earth and its Velocity.”
“The Relationship between Soil Porosity and Permeability.”
RESEARCH QUESTION
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Guides and centers your research - it should be clear and focused.
Include in this section why the answer to this question would be important to learn.
ALTERNATIVE HYPOTHESIS (Your original hypothesis)
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Predict what you expect the data to show and include the IV & DV in your statement
Does not need to be an “if/then” statement!
“Heat Absorption will be greater on surfaces with a darker color.”
“As a Galaxy’s distances from Earth increases, it velocity will increase.”
“There will be an increase in soil permeability with an increase in soil porosity.”
NULL HYPOTHESIS
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States that the independent variable has no effect on the dependent variable or that there is no
difference between the control group and the experimental group
STATISTICAL DATA TABLES
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Includes Descriptive Statistics and Statistical Analysis Tables (Completed in Excel)
What are Descriptive Statistics?
Statisticians describe a set of data in 2 ways
1. Compute a measure of central tendency (number that is most typical of the entire set of data)
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Mode - value that occurs most often (in a tie, use both)
Median - middle value when ranked highest to lowest
Mean - mathematical average
2. Describe variation (spread within the data - how closely the individual data points cluster around the mean)
 Range- difference between smallest & largest DV
 Standard Deviation - “Average” distance from the mean; the larger the standard deviation, the
more spread the data around the mean.
What is Statistical Analysis?
Scientists analyze data collected in an experiment to look for patterns or relationships among variables.
Statistical analysis allows scientists to test whether or not patterns are real, and not due to chance or
preconceived notions of the observer. We can never be 100% sure, but we can set some level of certainty to
our observations. A level of certainty accepted by most scientists is 95%. We will be using tests that allow us
to say we are 95% confident in our results.
Statistical Tests for Significance
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It limits the possibility that the data differences occurred by random chance or due to some unknown,
uncontrolled variable.
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If the data is shown to be statistically significant then the data differences can be explained by changes
in the independent variable.
Types of Statistical Tests - to determine if the data is statistically significant
1. The t-test:
 Used when you have two or more groups/sets and you want to compare measurements of each
group.
Ex: Do males and females differ in the amount of hours they spend studying in a given month?
2. The Chi-square test:
 Used when you have counts that can be placed into yes / no categories, or other simple categories
Ex: Which type of volcano is most prevalent at plate boundaries?
3. The Pearson R Correlation:
 Use to test how the values of one event or object relates to the values of another event or object.
Ex: Do nighttime temperatures affect the number of patients in an emergency room?
GRAPHS
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Includes a proper title, labeled x-axis and labeled y-axis (Completed in Excel)
RESULTS
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Describe the variables and method of research [include the time frame if applicable]
Summarize trends shown by the graph and explain the relevant descriptive data
Explain the results of the significance or correlation test
“Accept” the alternative hypothesis and “reject” the null hypothesis
or
“Fail to reject” the null hypothesis and ”reject” the alternative hypothesis
Is it statistically significant?
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The t-test and Chi-square test has an associated a p-value that would reflect how ‘comfortable’ is the
researcher in rejecting the null hypothesis in support of the alternative hypothesis. This ‘comfort zone’ is
attained when the p-value of a test statistic is below 0.05. If the p-value is not in the ‘comfort zone’ then
it is concluded that there is not statistical evidence to reject the null hypothesis.
We will use p-value < 0.05 which means that the probability of error in the research is 5/100
(or there’s 95% chance the results have no error).
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The Pearson R Correlation produces a result that will be between -1 and 1.
High correlation: R-Value = .5 to 1.0 or -0.5 to -1.0
Low correlation: R-Value = .1 to .3 or -0.1 to -0.3
What does it mean to “fail to reject” or “reject” the null hypothesis?
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If the alternative hypothesis is “rejected,” then you would “fail to reject” (same as accepting) the null
hypothesis. It means that any differences in your data are not significant and probably due to random
chance.
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If the alternative hypothesis is “accepted,” then you would “reject” the null hypothesis. It means that
there is a significant difference between your sets of data and these differences are due to the factors
(independent variable) that you changed.
The t-test and Chi-square test
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if p > 0.05 then ‘fail to reject the null hypothesis & reject the alternative hypothesis’
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if p < 0.05 then ‘reject the null hypothesis’ & accept the alternative hypothesis’
The Pearson R Correlation test
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if R-Value = .5 to 1.0 or -0.5 to -1.0 then ‘fail to reject the null hypothesis & reject the alternative
hypothesis’
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if R-Value = .1 to .3 or -0.1 to -0.3 then ‘reject the null hypothesis’ & accept the alternative hypothesis’
CONCLUSIONS
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Make a claim: Write a statement that answers the research question (Does the IV affect the DV?) and
share the findings
Explain the scientific concepts about the claim
Explain the results of the significance or correlation test
“Accept” the alternative hypothesis and “reject” the null hypothesis
or
“Fail to reject” the null hypothesis and ”reject” the alternative hypothesis
Discuss errors:
Every project is potentially flawed; think about what kind of things could have interfered with data
collection
Discuss further research:
How could you extend this research? What similar data could be studied?
PROOF READ:
 No personal pronouns – no “I” “You” “We” “Our” “Us”
 Use past tense and passive voice
 No contractions/abbreviations
 Be specific
 Use scientific vocabulary
 Capitalize proper nouns