Basic Statistics and Practical Pharmaceutical Applications

Lecture 1

An Introduction and Defining Variables

Objectives: Upon completion of this unit the learner should be able to:

1. Differentiate between descriptive and inferential statistics;
2. Determine if a variable is continuous or discrete;
3. Identify independent and dependent variables in a statistical problem set; and
4. Initiate the Excel data analysis option.

Lecture 2

Descriptive Statistics

Objectives: Upon completion of this unit the learner should be able to:

1. List the ways to describe information for sample data for a discrete variable;
2. List the ways to describe the central tendencies for a continuous variable sample; and
3. Use Excel to produce descriptive statistics for continuous data.

Lecture 3

Sampling

Objectives:  Upon completion of this unit the learner should be able to:

1. Discuss the advantages of using a random sample;
2. Use a random numbers table to select a sample; and
3. List probabilistic sampling methods

Lecture 4

An Introduction to Probability

Objectives:  Upon completion of this unit the learner should be able to:

1. Discuss the ways to determine probability for an event;
2. Explain conditional probability;
3. Differentiate between combinations and permutations; and
4. Describe and apply the binomial distribution.

Lecture 5

Confidence Intervals and Tolerance Limits

Objectives:  Upon completion of this unit the learner should be able to:

1. Describe the use of sample data to estimate population parameters;
2. Differentiate between the standard deviation and standard error for sample data;
3. Create confidence intervals using sample data when the population standard deviation is known or can be estimated; and
4. Describe tolerance intervals and how they differ from confidence intervals.

Lecture 6

Hypothesis Testing

Objectives:  Upon completion of this unit the learner should be able to:

1. Describe the difference between a null hypothesis and an alternative hypothesis;
2. Define Type I and Type II errors in hypothesis testing; and
3. List four factors that influence the power of a statistical procedure.

Lecture 7

Student t-tests

Objectives:  Upon completion of this unit the learner should be able to:

1. Define the degrees of freedom for a one-sample, two-sample t-test and paired t-test;
2. Calculate a confidence interval based on sample descriptive statistics;
3. Determine the significance of continuous dependent data for
   two levels of a discrete independent variable;
4. Identify paired versus unpaired data; and
5. Use Excel to calculate a two-sample t-test and a paired t-test.

Lecture 8

One-way Analysis of Variance and Post Hoc Procedures

Objectives:  Upon completion of this unit the learner should be able to:

1. Define the degrees of freedom associated with an analysis of variance;
2. Determine the significance of continuous dependent data for more than two levels of a discrete independent variable;
3. Use Excel to calculate a one-way analysis of variance;
4. Discuss why post hoc procedures are important in interpreting statistical results;
5. List appropriate post hoc procedure for a significant analysis of variance.

Lecture 9

N-way Analysis of Variance and Applications

Objectives:  Upon completion of this unit the learner should be able to:

1. Determine the degrees of freedom for an N-way analysis of variance;
2. Expand a two-way ANOVA to a measure of repeatability and reproducibility; and
3. Use Excel to calculate a two-way analysis of variance.

Lecture 10

Correlation and Linear

Objectives:  Upon completion of this unit the learner should be able to:

1. Define the difference between linear regression and correlation;
2. Identify the type of variables associated with a correlation and contrast with linear regression;
3. Determine the significance of a correlation coefficient;
4. Describe the type of variability that is identified by a regression line;
5. Evaluate the significance a linear regression calculation; and
6. Use Excel to calculate correlation and linear regression

Lecture 11

Chi Square and Related Tests

Objectives:  Upon completion of this unit the learner should be able to:

1. Describe the use of the chi square test of independence when trying to evaluate the relationship between two discrete variables;
2. Identify the number of degrees of freedom for various sizes of contingency table;
3. Discuss the reasons for using a McNemar test; and
4. Discuss the reasons for using a Fisher’s exact test.

Lecture 12

Nonparametric Tests

Objectives:  Upon completion of this unit the learner should be able to:

1. Describe the reasons why nonparametric test may be preferred over traditional parametric procedures;
2. Identify nonparametric alternatives for the Student t-tests, one-way ANOVA and correlation; and
3. Discuss the ranking procedure required for most nonparametric procedures.

Lecture 13

Drug Product - Analytical Controls for Different Dosage Forms - Setting Specifications for the Certificate of Analysis

Objectives:  Upon completion of this unit the learner should be able to:

1. Describe how outlier tests can be used to determine if there is an aberrant value;
2. Define the difference between an outlier and an influential data point; and
3. Apply some of the most commonly used outlier tests