STEM Fair Graphs & Statistical Analysis. Objectives: – Today I will be able to: Construct an...
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Transcript of STEM Fair Graphs & Statistical Analysis. Objectives: – Today I will be able to: Construct an...
![Page 1: STEM Fair Graphs & Statistical Analysis. Objectives: – Today I will be able to: Construct an appropriate graph for my STEM fair data Evaluate the statistical.](https://reader036.fdocuments.in/reader036/viewer/2022062801/56649e795503460f94b79350/html5/thumbnails/1.jpg)
STEM Fair Graphs & Statistical Analysis
![Page 2: STEM Fair Graphs & Statistical Analysis. Objectives: – Today I will be able to: Construct an appropriate graph for my STEM fair data Evaluate the statistical.](https://reader036.fdocuments.in/reader036/viewer/2022062801/56649e795503460f94b79350/html5/thumbnails/2.jpg)
• Objectives:– Today I will be able to:
• Construct an appropriate graph for my STEM fair data• Evaluate the statistical significance of my data using the appropriate
statistical test
• Informal Assessment – students questions and responses to STEM Fair Discussions
• Formal Assessment – STEM fair data collection and analysis rubric
• Common Core Connection – Value Evidence– Use technology and digital media strategically and capably
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Lesson Sequence
• Evaluate: Warm-Up• Explain: Pass out STEM Fair Checklist• Explain: Pass out STEM Fair Data Collection
and Analysis Rubric• Explain/ Evaluate: Review Data,Graphing and
Statistics Expectations• Evaluate: Exit Ticket
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Warm - Up
• Convert the speed of 60 miles/ hour to meters/second.
Note (): – 1 mile = 5280 feet– 3.28 feet = 1 meter
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Objectives
• Today I will be able to:– Construct an appropriate graph for my STEM fair
data– Evaluate the statistical significance of my data
using the appropriate statistical test
![Page 6: STEM Fair Graphs & Statistical Analysis. Objectives: – Today I will be able to: Construct an appropriate graph for my STEM fair data Evaluate the statistical.](https://reader036.fdocuments.in/reader036/viewer/2022062801/56649e795503460f94b79350/html5/thumbnails/6.jpg)
Homework
• Study for the Lab Equipment and Safety Quiz tomorrow
• Work on STEM fair Data Analysis Section
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Agenda
• Warm-Up• Pass out STEM Fair Checklist• Pass out STEM Fair Data Collection and
Analysis Rubric• Review Data,Graphing and Statistics
Expectations• Exit Ticket
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Pass out STEM Fair Checklist and Data Collection and Analysis
Rubric
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Data
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Data Tables
• Make sure the data tables include:– A title– Appropriate labels and SI units for both the
dependent and independent variables– Averages of data
• Your graphs should be a representation of the averages of your data! Not all the data that you collect!
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Graphs
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What type of graph should I use to analyze my data?
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Types of graphs• Pie Chart
– Used to compare parts to a whole (percentages)
• Bar Graph– compare values in a
category or between categories. Multiple bar graphs compare relationships of closely related data sets. These graphs may be used to demonstrate relationships in non-continuous data or data intervals.
DO NOT use for your STEM project
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Types of Graphs Continued• Time-Series Plot
– dependent variable is numerical and the independent variable is time
• XY Line Graph – dependent and independent
variables when both are numerical and the dependent variable is a function of the independent variable
• Scatter plot– Shows how two variables
MAY be related to one another
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Why do I need error bars on my graph?
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Error bars
• Show variability in data• Indicate error and/or uncertainty in measurement• A larger size error bar means the
measurement/ data collected is not as accurate
• Error bars should be one standard deviation in length
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What is standard deviation?
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Standard Deviation
• Determines validity of data set for each testing group
• If data points are close to the average, there is a small standard deviation and the data is valid
• If the standard deviation is large, the data points are not close to the average and the validity of the data is questioned
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What is the coefficient of correlation (r)?
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Coefficient of Correlation (r)
• used to fit a straight line (best-fit) to sample data to summarize the relationship between x and y values.
• Sample correlation coefficient (r) is calculated to measure the extent to which x and y are linearly related.– Example would be looking at the relationship between %
salinity in water (x) and nitrate level (y). • Example of results would be that a simple linear regression
model explained 91.3% of total variation in nitrate level by relating it to salinity
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Coefficient of Correlation (r)• Only use if graph is a line graph or scatterplot (not for time
series)• Describes the direction and strength of 2 sets of variables• Calculate when the line of best fit is made on a graph in
excel• R Values
– Positive Correlation = Direct relationship for data – Negative correlation = Indirect relationship for data– r = 0, no correlation– r < 0.5, weak correlation – r > 0.8, strong correlation – r = 1 perfect correlation
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Coefficient of Correlation examples
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STEM Fair: Statistical Analysis
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Summary Statistics• Mean – represents population mean (calculated
same as the average)• Standard Deviation – shows the variability of an
observation in a sample
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Summary Statistics Cont.
• Confidence Interval - the width of the interval shows how precisely the value of the mean is known
• Shows the degree of confidence that our mean is between two values
• typically a 95% CI is used
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Steps to Completing Statistical Analysis1. Data collection & input2. Data summary & reduction3. Data analysis: Perform statistical test(s) and draw
conclusion
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Drill
• What is an independent variable?
• What is a dependent variable
• What is a control?
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Types of graphs• Pie Chart
– Used to compare parts to a whole (percentages)
• Bar Graph– compare values in a
category or between categories. Multiple bar graphs compare relationships of closely related data sets. These graphs may be used to demonstrate relationships in non-continuous data or data intervals.
Sadly, Bar Graphs May be Used
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Types of Graphs Continued• Time-Series Plot
– dependent variable is numerical and the independent variable is time
• XY Line Graph – dependent and independent
variables when both are numerical and the dependent variable is a function of the independent variable
• Scatter plot– Shows how two variables
MAY be related to one another
![Page 30: STEM Fair Graphs & Statistical Analysis. Objectives: – Today I will be able to: Construct an appropriate graph for my STEM fair data Evaluate the statistical.](https://reader036.fdocuments.in/reader036/viewer/2022062801/56649e795503460f94b79350/html5/thumbnails/30.jpg)
Test Assumptions• Most statistical tests have assumptions that should
be met such as:• Data follows a normal population distribution &• Large enough sample size to detect change.• We are ignoring statistical test assumptions for this
project.
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Types of Statistical Tests
• Paired T-Test• Unpaired T-Test• ANOVA• Chi-Square• Coefficient of Correlation
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T-TestsThis test is used to compare the data from two different
testing groups to determine if they are significantly different. There are two different types:
PAIRED: Used when the data consist of pairs of observations on the same person or object.
• Example: comparing the heart rate of individuals before and after watching a scary movie.
UNPAIRED: Used when the data from one group are not directly linked to the data of the other group.
• Example: comparing the effect of red light versus blue light on the growth of plants.
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ANOVA
This test is used to determine whether there are any significant differences between the means of three or more independent (unrelated) groups.
• Example: determining whether exam performance differed based on test anxiety levels amongst students. Students are divided into three independent groups (e.g., low, medium and high-stressed students).
• Most of you will be doing this type of test!
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Chi-Square TestThis test is used to determine if there are differences
between two or more frequency distributions. Both independent and dependent variables need to be categorical data.
• Example: comparing the foraging height (upper, middle, and lower) of yellow warblers in different tree species (oak, maple, aspen, and hazel).
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Analyzing the Test Results• Two possible conclusions after carrying out a test– Reject Hypothesis– Fail to reject Hypothesis (we can never accept the
alternative hypothesis)
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Analyzing the Test Results (cont.)• P-values – one way to report the result of an analysis is
by saying whether or not the hypothesis was rejected at a specified level of significance (we will use .05)
• The smaller the calculated p-value, the greater the difference between the groups.
• Example: the difference in means from our testing groups is statistically significant at the .05
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Discuss with a partner
• What type of statistical test should I use to analyze my data?
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STEM Fair Data Collection and Analysis Due: September 27
• Mr. Klotz’s Expectations:– Data Tables– Appropriate Graphs– Complete Statistical Analysis Worksheet and Place
in the Folder
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Exit Ticket
• What questions do you have about the Data Collection and Analysis Section?