How much calculus is used in statistics?

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SUMMARY

The discussion centers on the calculus requirements for a statistical methods course, specifically referencing MTH 182 (Calculus II) as a prerequisite. Participants confirm that calculus, particularly multivariable calculus and matrix operations, is essential for understanding continuous distributions and their applications in statistics. Key topics include the central limit theorem, hypothesis testing, and the use of statistical software for data analysis. The conversation emphasizes the necessity of calculus for evaluating integrals and approximating distributions.

PREREQUISITES
  • MTH 182 (Calculus II)
  • 200-level mathematics course (e.g., Multivariable Calculus, Linear Algebra)
  • Understanding of continuous and discrete random variables
  • Familiarity with statistical software for data analysis
NEXT STEPS
  • Explore the central limit theorem and its implications in statistics
  • Study hypothesis testing methods, including chi-square and t-tests
  • Learn about continuous distributions and their applications in statistical analysis
  • Investigate the use of statistical software for performing regression analysis
USEFUL FOR

Students in mathematics, statistics, or physics, particularly those looking to enhance their understanding of statistical methods and the calculus involved in data analysis.

Wm_Davies
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I am a physics major and unfortunately this semester there is almost no classes that I can take in my major field of study due to not having the proper prerequisites. So I am looking for a course that will keep my math skills honed. I am really interested in taking statistical methods which seems like it will involve calc and certainly matrices. How much calc is generally involved in a statistical methods course?

The course description is as follows:

FYI: MTH 182 is Calculus II and I have taken two 200 level math courses (Multivariable Calculus and Linear Algebra).

Prerequisites: MTH 182 and a 200-level mathematics course. Issues of data collection, use and misuse, graphical and numerical summary techniques, basic probability, discrete random variables, continuous random variables, central limit theorem, confidence intervals, hypothesis testing of a proportion, hypothesis testing of a mean, 2 sample hypothesis testing, chi square testing, regression. Appropriate statistical software used extensively.
 
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Wm_Davies said:
I am a physics major and unfortunately this semester there is almost no classes that I can take in my major field of study due to not having the proper prerequisites. So I am looking for a course that will keep my math skills honed. I am really interested in taking statistical methods which seems like it will involve calc and certainly matrices. How much calc is generally involved in a statistical methods course?

The course description is as follows:

FYI: MTH 182 is Calculus II and I have taken two 200 level math courses (Multivariable Calculus and Linear Algebra).

Prerequisites: MTH 182 and a 200-level mathematics course. Issues of data collection, use and misuse, graphical and numerical summary techniques, basic probability, discrete random variables, continuous random variables, central limit theorem, confidence intervals, hypothesis testing of a proportion, hypothesis testing of a mean, 2 sample hypothesis testing, chi square testing, regression. Appropriate statistical software used extensively.

Hey there.

Anything involving continuous distributions will get you using calculus.

Anything involving multivariable distributions will get you using multivariable calculus and as such will get you using matrices.

Also some stuff with discrete will get you using continuous distributions in the case of the central limit theorem and approximating distributions such as large binomial distributions (which are discrete) by using normal approximations with so called "continuity correction".

Some of the time you will have to evaluate integrals, but they won't have closed form analytical expressions so you will use tables especially when you are doing "statistics" over just probability calculations where you use normal, gamma and student t distributions.
 
That definitely makes sense! Thanks! :)
 

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