This lesson covers definitions, variable types, measurement scales, and the difference between qualitative and quantitative variables.
This chapter covers creating frequency distributions including categorical data, relative and cumulative frequencies. It also explains how to determine the number of classes and the interval for creating frequency distributions from large datasets with continuous variables.
This chapter This lesson continues with descriptive statistics and introduces the mean for populations and samples. It also discusses locating the median for datasets with an even and odd number of observations. It also discusses finding the mode and dataset with more than one mode. It covers measures of dispersion including the Range, Population and Sample Variance, Population and Sample Standard Deviation, and the Empirical Rule.
This chapter covers finding the location and values for percentiles, skewness, and determining correlations with a scatterplot.
This chapter explains probability terminology and discusses how to compute probability for dependent and independent events as well as conditional probability. It also explains the use of the Combination and Permutation formulas.
This chapter covers creating and using discrete, binomial, and Poisson probability distributions. It also covers computing the mean and variance and uses simple examples to explain these concepts..
This chapter covers computing the mean of a uniform continuous distribution. It also covers computing Z scores and locating the area under the curve that equates to the area for the z score.
This chapter covers simple random sampling, systematic random sampling, sampling error, sampling distribution of the sample mean, the central limit theorem, and computing a z score from a sample mean.
This Chapter 9 covers Point Estimates, Confidence intervals and shows how to compute a margin of error using both z and t scores. It also discusses how to determine the correct sample size
This chapter introduces the 5-step hypothesis testing procedure that can be used with many test statistics. Specifically, this chapter covers Z and T.
This chapter uses the 5-step hypothesis testing procedure for two samples or proportions.
This chapter explains the ANOVA computation with two or more variances.
This chapter explains computing the Correlation Coefficient, dependent and independent variables and performing linear regression manually and with Excel.
This chapter explains computing the goodness of fit for equal and unequal frequency distributions.
