In this lecture, you will learn about the elements of a measurement system and how each of them impact the data you are to collect. ​Difficulty Level : Medium

​In this lecture, you will learn about accuracy and resolution. At the end of lecture, you will be able to assess the accuracy and resolution of a gage. Difficulty Level : Medium

​In this lecture, you will learn about precision. At the end of lecture, you will be able to differentiate between accuracy and precision. Difficulty Level : High

​In this lecture, you will learn about discrete Gage R&R. At the end of lecture, you will be able to assess the Gage R&R of discrete gages and qualify them for further usage. Difficulty Level : High

In this lecture, you will learn about skewness and kurtosis, two important shape parameters of any distributions. At the end of the lecture, you will be able to assess any distribution for its skewness and kurtosis. Difficulty Level: Medium

In this lecture, you will learn about different types of data and will be able to associate what type of data is being used in a given scenario. Difficulty Level : Medium

In this lecture, you will learn about different types of measurement scales and will be able to associate what type of measurement scale is being used in a given scenario. Difficulty Level : Medium

In this lecture, you will be learn about the significance of data collection in improvement projects. At the end of the lecture, you will be able to get a good perspective how how to go about collecting data for a given project or scenario. Difficulty Level : Medium​

​In this lecture, you will be learn to plan for data collection. At the end of the lecture, you will be able to complete formal data collection plan, step-by-step. Difficulty Level : Medium

In this lecture, you will learn to format in which data has to be collected so that meaningful analysis and inference can be drawn from it. Difficulty Level : Low

In this lecture, you will learn about the need for sampling and broadly the various methods of sampling. At the end of the lecture you will be able to decide between population and process sampling, which method is to adopted in a given scenario. Difficulty Level : Low

In this lecture, you will understand population sampling in detail. You will also learn about various methods of population sampling and how to choose an appropriate population sampling method for a given scenario. Difficulity Level : Medium

In this lecture, you will understand process sampling in detail. You will also learn about various methods of process sampling and how to choose an appropriate process sampling method for a given scenario. ​Difficulity Level : Medium​

In this lecture, you will understand factors influencing the sample size, in general and particularly discrete data and formula for computation of sample size. At the end of this lecture, you can compute the sample size for discrete data. Difficulty Level : High

In this lecture, you will understand factors influencing the continuous sample size and formula for computation of sample size. At the end of this lecture, you can compute the sample size for continuous data. Difficulty Level : High

In this lecture, you will learn about how statistics is classified into two types and how each of these are useful to business in decision making. At the end of the lecture, you will be able to decide which type of statistics is useful in a given scenario. Difficulty Level : Medium

In this lecture, you will learn about what is a histogram and how is it constructed. Difficulty Level : Medium

In this lecture, you will learn how to draw meaningful inferences about the data and its implications to business. Difficulty Level:Medium

In this lecture, through a scenario you will appreciate how histogram can be used in business to drive performance. ​Difficulty Level : Low

In this lecture, you will learn about probability distributions and how to interpret them. Difficulty Level : High

In this lecture, you will learn about measures of central tendency and how they are useful to understand the nature of any data set. Difficulty Level: Low

In this lecture, you will learn about measures of dispersion and how they are useful to understand the nature of any data set. Difficulty Level: Medium

​In this lecture, you will learn about normal distribution and the principle of normal distribution. Difficulty Level : High

In this lecture, you will learn about outliers and how they are used in business to drive performance. Difficulty Level: Medium

In this lecture, you will learn about concepts of Confidence Level and Intervals and their relevance to descriptive statistics and statistics, in general. At the end of the lecture, you will be able to appreciate how these concepts assume importance during statistical analysis. Further you will be able to decide the apt confidence levels for any given scenario. Difficulty Level : High

In this lecture you are introduced to Minitab, a statistical software package which is extensively used for statistical analysis. 1) An external link to Minitab site to install 30 day trial version of minitab is included in resource 2) A external video on Getting Started with Minitab 17 is included in resource

In this lecture, you will learn about descriptive statistics in general that summarizes the concepts you learnt in this section. At the end of lecture, you will be able to interpret descriptive statistics of any data set and drive necessary inferences. Difficulty Level: Medium

In this lecture, you will learn about Anderson-Darling Normality Test which is used to evaluate the normality of any probability distribution. At the end of this lecture, you will be able to assess the normality of any given distribution using Anderson-Darling Test. Difficulty Level: Medium

In this lecture, you will learn about Box and Whisker Plots and how they are used for graphical analysis. At the end of this lecture, be able to plot Box Plot and interpret it. Difficulty Level : Medium

​In this lecture, you will learn about Stem and Leaf Plots and how they are used for graphical analysis. At the end of this lecture, be able to plot Stem and Leaf​ Plot and interpret it. Difficulty Level : Medium

​​In this lecture, you will learn about Run Charts and how they are used for graphical analysis. Difficulty Level : Medium

In this lecture, you will understand 4 significant patterns in any trend chart, their identification and inference . Difficulty Level: Medium

In this lecture, you will learn to use a Run Table to identify patterns in data. At the end of the lecture, you will be able to create, analyze and ideate in any scenario. Difficulty Level: Medium

In this lecture, through a scenario you will appreciate how Run Charts can be used in business to drive performance. Difficulty Level : Low

In this lecture, you will be introduced to the concept of statistical hypothesis testing and its need. Difficulty Level : High

“​In this lecture, you will be learn about statistical hypothesis statements. At the end this lecture, you will be able to frame suitable hypothesis statements in any scenario. Difficulty Level : High”

​​In this lecture, you will be learn about statistical and practical significance in hypothesis tests. At the end this lecture, you will be able to appreciate the role of statistical significance in any scenario. Difficulty Level : High

​​In this lecture, you will be learn about test statistic. At the end this lecture, you will be able to appreciate the role of test statistic in any hypothesis testing scenario. Difficulty Level : High

​​In this lecture, you will be learn about Critical statistic. At the end this lecture, you will be able to appreciate the role of Critical statistic in any hypothesis testing scenario. Difficulty Level : High

​​In this lecture, you will be learn about p-value. At the end this lecture, you will be able to appreciate the role of p-value in any hypothesis testing scenario. Difficulty Level : High

​​In this lecture, you will be learn about errors in hypothesis testing. At the end this lecture, you will be able to appreciate the role of errors in hypothesis testing in any hypothesis testing scenario. Difficulty Level : High

​​In this lecture, you will be learn about various hypothesis tests. At the end this lecture, you will be able to select an appreciate hypothesis test for scenario. Difficulty Level : High

​​In this lecture, you will be learn about various hypothesis tests for means. At the end this lecture, you will be able to select an appreciate hypothesis mean test for scenario. Difficulty Level : High

​In this lecture, you will be learn about ANOVA. At the end this lecture, you will be able to select and perform an ANOVA for suitable scenario. Difficulty Level : High

In this lecture, you will be learn about Chi-square Test. At the end this lecture, you will be able to select and perform an Chi-square Test for suitable scenario. Difficulty Level : High

​​In this lecture, you will be learn about various hypothesis tests for proportions. At the end this lecture, you will be able to select an appreciate hypothesis proportions​ test for scenario. Difficulty Level : High

In this lecture, you will be learn about scatter diagram. At the end this lecture, you will be able to create scatter diagram​ test for scenario. Difficulty Level : High

In this lecture, through a scenario you will appreciate how scatter diagrams can be used in business to drive performance. Difficulty Level : Low

​In this lecture, you will be learn about correlation coefficient. At the end this lecture, you will be able to create correlation coefficient​ test for scenario. Difficulty Level : Medium

In this lecture, you will be learn about linear regression. At the end this lecture, you will be able to create linear regression​ for scenario. Difficulty Level : High