Statistics (MA223)
Rose-Hulman Institute Of Technology
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includes Rstudio code that imports data, creates a model of the data, estimates the models parameters with specific confidence interval, calculates error in model, makes a conclusion
includes Rstudio code that imports data, plots data, models data for two hypotheses, compares models, finds p-value and error, makes a conclusion
Includes Rstudio code that imports data, creates an ANOVA model of the data, get the diagnostics for the data, plots the model, makes a conclusion
includes Rstudio code that imports data, plots the data, creates anova models for both hypotheses, compares anova models, calculates p-value and error , makes a conclusion
includes Rstudio code that reads data, creates a model, obtains diagnostics, creates a plot and makes a conclusion
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Includes rstudio code to import and analyze data, perform and anova analysis for different models, compare the models, estimate parameters, and make a conclusion
ANOVA analysis on Rstudio. Includes code to read and separate data, and create a plot. includes conclusions from plot
![Statistical Analysis of Paper Airplanes](/docpics/2772935/646811bf24aa9_2772935_121_171.jpeg)
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Statistical Analysis of Paper Airplanes
- Andere • 6 Seiten • 2023
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Question 1: Parameter(s) Define the population parameter(s) of interest associated with the research objective. Include both the definition in the context of the problem as well as the symbol you will use to represent this parameter. Our population parameters are the average distance flown by a particular design of airplane. Since we have three designs, the symbols we will use for this are μ_1,μ_2, and μ_3. Question 2: Variables State the response and any other variables (including un...
![Null Distributions](/docpics/2772919/646811b17f103_2772919_121_171.jpeg)
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Null Distributions
- Notizen • 4 Seiten • 2023
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nataliedillon
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One of the most important steps in any statistical analysis is accounting for the variability in our estimate of the parameter of interest. Last week, we saw this through the lens of a sampling distribution. This week, we will see that if we want to find evidence against a hypothesis, we must determine the value of the statistic (or standardized statistic) we expect when the null hypothesis is true while accounting for the variability in our statistic. This leads to the null distribution. This a...
includes Rstudio code that imports data, creates a model of the data, estimates the models parameters with specific confidence interval, calculates error in model, makes a conclusion
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