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Introduction to Statistics

SigmaXL Overview

Ron Pereira offers an overview of Sig­maXL includ­ing how to nav­i­gate through the dif­fer­ent menus and how to best lever­age Sig­maXL’s amaz­ing Help menu.

Course Videos

1

Introduction to Statistics

3:30

 2

Data Types

3:48Members only

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  • Introduction to Six Sigma

    • 4 Videos
    • 17m
    Six Sig­ma is a data-dri­ven approach to improv­ing qual­i­ty and effi­cien­cy in busi­ness process­es. Six Sig­ma aims for near-per­fect per­for­mance, tar­get­ing a goal of no more than 3.4 defects per mil­lion oppor­tu­ni­ties. The method­ol­o­gy employs the frame­work of DMA­IC (Define, Mea­sure, Ana­lyze, Improve, Con­trol) for deliv­er­ing improve­ment projects. Six Sig­ma prac­ti­tion­ers use sta­tis­ti­cal tools to iden­ti­fy root caus­es of defects and inef­fi­cien­cies, enabling pre­cise solu­tions that improve out­comes, increase cus­tomer sat­is­fac­tion, and con­tribute sig­nif­i­cant­ly to orga­ni­za­tion­al cost reduc­tion and profitability.

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  • Project Selection

    • 8 Videos
    • 56m
    Now that we’ve cov­ered some impor­tant foun­da­tion­al work it’s time to learn how to iden­ti­fy a good project. This step is extreme­ly impor­tant since a poor­ly scoped project has lit­tle hope of success.

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  • Process Mapping & Selected Tools

    • 7 Videos
    • 38m
    The abil­i­ty to under­stand how mate­r­i­al and process­es flow, while also iden­ti­fy­ing the ​“inputs” or ​“Xs” to a process, is at the heart of the DMA­IC method­ol­o­gy. So, in this sec­tion we’ll learn about dif­fer­ent types of process maps while also learn­ing how to take the infor­ma­tion learned from process map­ping into addi­tion­al tools like the C&E Matrix and FMEA in order to nar­row the lists of inputs down to the ​“crit­i­cal few.” To be sure, many prob­lems can be solved dur­ing this phase of a project, so it’s real­ly time to dig in!

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  • Introduction to Statistics

    • 2 Videos
    • 6m
    Sta­tis­tics is the sci­ence of col­lect­ing, ana­lyz­ing, pre­sent­ing, and inter­pret­ing data. Sta­tis­tics pro­vides meth­ods for design­ing exper­i­ments, tech­niques for ana­lyz­ing data, and mak­ing informed deci­sions. Learn the dif­fer­ences between descrip­tive and infer­en­tial sta­tis­tics, and how to use each. This dis­ci­pline is essen­tial for enabling pro­fes­sion­als and researchers to eval­u­ate trends, test the­o­ries, and dri­ve improve­ment and inno­va­tion in any industry.

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  • Descriptive Statistics

    • 1 Videos
    • 6m
    Accu­rate­ly inter­pret­ing data col­lect­ed dur­ing test­ing phas­es is cru­cial for enhanc­ing process­es and work­flows. Descrip­tive sta­tis­tics are sum­ma­ry mea­sures that describe, show, or sum­ma­rize the char­ac­ter­is­tics of data in a mean­ing­ful way. Ensur­ing that all team mem­bers are pro­fi­cient in descrip­tive sta­tis­tics and their prop­er appli­ca­tion, we can make informed deci­sions that dri­ve per­for­mance improvements. 

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  • Graphs & Charts

    • 1 Videos
    • 8m
    When it comes to see­ing how process­es change over time, the abil­i­ty to graph and make charts of data can be invalu­able, espe­cial­ly for con­tin­u­ous improve­ment prac­ti­tion­ers. Graphs and charts can even help empha­size dif­fer­ent attrib­ut­es of the same data. But how do we know if we’re using the best visu­als for our par­tic­u­lar data set? This course will help with that decision.

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  • Inferential Statistics

    • 38 Videos
    • 2h 32m
    Hav­ing a sol­id under­stand­ing of the sci­en­tif­ic method and how to study a small sam­ple of data in order to make deci­sions about an entire pop­u­la­tion is what usu­al­ly sep­a­rates excel­lent Con­tin­u­ous Improve­ment Prac­ti­tion­ers from aver­age ones. In the next series of videos we real­ly dig into top­ics such as hypoth­e­sis test­ing and nor­mal­i­ty. Final­ly, you will nev­er need to use ALL of these tools in a sin­gle project… but it’s still impor­tant you under­stand the tool allow­ing you to use it when the time is right.

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  • Statistical Process Control

    • 2 Courses
    • 28 Videos
    Sta­tis­ti­cal Process Con­trol, or SPC, is a method to mon­i­tor, con­trol, and enhance process­es. SPC enables us to build con­sis­tent, pre­dictable process­es by study­ing data over time and min­i­miz­ing vari­a­tion. Learn the five steps of Sta­tis­ti­cal Process Con­trol, how to cre­ate a sam­pling plan, set sub­group sizes and sam­ple sizes, the dif­fer­ence between attribute and vari­able data, how to select and cre­ate the appro­pri­ate type of Con­trol Chart for each sit­u­a­tion, and more.

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  • Process Capability

    • 9 Videos
    • 46m
    Have you ever won­dered what ​“Six Sig­ma” real­ly means from a sta­tis­ti­cal per­spec­tive? If so, you’re about to learn. Addi­tion­al­ly, you’re also going to learn the key rela­tion­ship between the Voice of the Cus­tomer and the Voice of Process as well as how to mea­sure this rela­tion­ship with Process Capa­bil­i­ty Analysis.

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  • ANOVA

    • 7 Videos
    • 47m
    ANO­VA, which stands for Analy­sis of Vari­ance, is a fun­da­men­tal sta­tis­ti­cal con­cept that is used in things such as Mea­sure­ment Sys­tems Analy­sis, Regres­sion, and DOE. In this sec­tion, we’ll learn what ANO­VA is as well as how we can lever­age it in order to run experiments.

    View Course

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