NURS/HSCI 597:  Approaches to Data Analysis

 
 

Instructors

Heibatollah Baghi, Ph.D.

Mastee Badii, Ph.D. Candidate

Office Hours: Tues. & Wed. 10:00 – 12 Noon

By Appointment

COURSE DESCRIPTION

This course examines univariate and bivariate procedures appropriate for analyzing nursing research data. Emphases are on selecting, applying, and computerizing procedures in relation to the level of data and type and size of the sample in nursing research.

TEXTBOOKS

  1. D. F. Polit (1996). Data Analysis & Statistics for Nursing Research. Upper Saddle River, NJ: Prentice-Hall, Inc. (Required)
  2. M. J. Norusis (2006). SPSS 14.0 Guide to Data Analysis. Upper Saddle River, NJ: Prentice-Hall, Inc. (Required)
  3. SPSS Inc. (2006). SPSS 14.0 for Windows Student Version. (Version 4). Upper Saddle River, NJ: Prentice-Hall, Inc. (Unless you have frequent and easy access to a GMU computer lab or another computer with SPSS software, you need to purchase this. We will use SPSS weekly and you will need it for homework. SPSS 15.0 will be available soon but 14.0 is preferable for this course. If you don’t have access to a PC and were planning to use an Apple computer for this course, contact me.)

SPSS 14.0 is the most up-to-date software currently available. If you do not have access to GMU campus computers with SPSS (SPSS is available on all computers labs at the GMU computers) it can be purchased and installed on your computer. The student version is sufficient for the course.

COURSE OBJECTIVES

By the end of this course, the students will be able to:

  1. Identify the measurement scale (level of data) on which healthcare data are collected.
  2. Discuss the purposes of descriptive and inferential statistics.
  3. Describe the sampling distributions and discuss their use in inferential statistics.
  4. Differentiate between parametric and nonparametric tests.
  5. Perform various parametric statistical tests including one-sample z-test, one-sample t-test, two independent samples, two dependent samples and Pearson correlation coefficient.
  6. Interpret the components in a one-way analysis of variance (ANOVA).
  7. Identify the elements in the simple regression equation model.
  8. Run SPSS for univariate and bivariate statistical tests and interpret the results.
  9. Perform various nonparametric tests including Chi-square test, the Mann-Whitney test, the sign test and the Spearman rank correlation.
  10. Use selected graphics program for presenting healthcare research data.

EVALUATION

  • Class Attendance and Participation (10 points)
  • Quizzes (15 points)
  • Written homework assignments (85 points)
  • Research Project (15 points)
  • Final exam (25 points)

GRADING SCALE

Scores  Percentage  Grade
 141 – 150  94 –100  A
 135 - 140  90 – 93  A-
 130 - 134  87 – 89  B+
 125 - 129  83 – 86  B
 120 - 124  80 – 82  B-
 111 - 119  74 – 79  C

CLASS SCHEDULE

Jan 30
Topic 1 Introduction:  Goals of the course.

  • Research Variables,
  • Scales of Measurement.
  • The Uses of Data Analysis;
  • An overview of SPSS 13.0 (Data Analysis & Statistics Ch. 1; SPSS 13.0 Guide to Data Analysis Ch. 2)

Feb 6
Topic 2 Descriptive Statistics for Univariate Sample Data

  • Frequency Tables,
  • Graphic Display of Frequency Distributions: Pie and Bar Charts and Histograms.
  • (Data Analysis & Statistics Ch. 2; SPSS 13.0 Guide to Data Analysis Ch. 4)

Feb 13
Topic 3 Descriptive Statistics for Univariate Sample Data

  • Measures of Central Tendency and Variability;
  • Applications of Central Tendency and Variability.
  • (Data Analysis & Statistics Ch. 3, pp 43-55; SPSS Guide to Data Analysis Ch.5)

Feb 20
Topic 3 Normal Distributions and Standard Scores

  • Properties of the Normal Distribution;
  • Areas under the Normal Curve.
  • Data Analysis & Statistics Ch. 3, pp 56 - 67;
  • SPSS 13.0 Guide to Data Analysis Ch. 11, pp.213-218 and 225 - 231.
  • Quiz # 1: Descriptive Statistics

Feb 27
Topic 4 Bivariate Descriptive Statistics

  • Cross-tabulation;
  • the Covariance,
  • the Pearson’s r, and Coefficient of Determination.
  • (Data Analysis & Statistics Ch. 4; SPSS Guide to Data Analysis Ch. 21, pp. 488- 490.)

 Mar 6
Topic  5 Inferential Statistics: Normal Distribution

  • Sampling Distribution II of Means;
  • Hypothesis Testing;
  • Estimation of Parameters for Normal Distribution.
  • (Data Analysis & Statistics Ch.5; SPSS13.0 Guide to Data Analysis Ch.11)

Mar 13
Topic 5 Hypothesis Testing and Interval Estimation Using Student t Distribution

  • Steps in Hypothesis Testing;
  • One-Sample Significance Testing;
  • Point Estimates, and Confidence intervals.
  • (Data Analysis & Statistics Ch. 5; SPSS Guide to Data Analysis Ch. 12)
  • Quiz # 2: Pearson Correlation.

Mar 20
Topic 6 Comparing the Means of Two Populations

  • The t Test for 2 Independent Samples;
  • Determination of Sample Size.
  • (Data Analysis & Statistics Ch. 6, pp. 127-134; SPSS 13.0 Guide to Data Analysis Ch. 14)

Mar 27
Topic 6 Comparing the Means of Dependent Samples.

  • The t Test for Two Dependent Samples.
  • (Data Analysis & Statistics Ch. 6, pp. 134-153; SPSS 13.0 Guide to Data Analysis Ch.13)

Apr 3
Topic 7 Comparing the Means of Three or More Independent Samples

  • ANOVA; Power Analysis in an ANOVA Context.
  • (Data Analysis & Statistics Ch. 7, pp. 155-165 & 173-180; SPSS Guide to Data Analysis Ch.15)

Apr 10
Topic 9 Inferences about the Pearson Product Moment Correlation.

  • Coefficient. Statistical Power and Selecting an Appropriate Sample Size.
  • (Data Analysis & Statistics Ch. 9 pp. 225 - 234)

Apr 17
Topic 9 Regression and Prediction

  • Correlation, Prediction, Regression and Sums of Squares.
  • (Data Analysis & Statistics Ch. 9 pp. 237-255; SPSS 13.0 Guide to Data Analysis Ch. 20)
  • Quiz # 3: ANOVA

Apr 24
Topic 8 Measures of Association for Nominal Data

  • The χ2 Test of Independence;
  • (Data Analysis & Statistics Ch. 8 pp. 193-202; SPSS 13.0 Guide to Data Analysis Ch. 17)

May 1
Topic 8 Parametric Versus Nonparametric Tests.

  • Course/Faculty Evaluation.
  • (Data Analysis & Statistics Ch. 8 pp. 202-222; SPSS 13.0 Guide to Data Analysis Ch. 18 pp. 383-400)

May 8 Final Exams.

SPECIFIC COURSE OBJECTIVES

These objectives should be used to guide your reading of the material and preparation for exam.

Topic Objectives
1 Demonstrate the various ways of running SPSS for Windows: Menus and Syntax commands and indicate when each method is most appropriate.
1 Illustrate how SPSS for Windows can select and transform data in the Data Editor in order to facilitate data analysis.
1 Demonstrate how to open an existing data file, to read ASCII data files, and to enter data into SPSS for Windows.
1 Define measurements scales and discuss the properties of each scale; explain the appropriateness of each scale to statistical testing methods.
1 Distinguish between descriptive and inferential statistics.
2 Differentiate among Univariate, Bivariate, and Multivariate statistics.
2 Select appropriate procedures for summarizing distributions and describing Univariate sample data and bivariate association.
1 & 2  Distinguish between dependent and independent variables.
1 & 2  Distinguish between discrete and continuous variables.
2  Interpret data presented in bar charts, pie charts, and histograms.
2  Indicate the appropriate types of graphs that can be used for displaying data.
3  Compute measures of central tendency: mean, median, and mode.
3  Compute measures of variation: range, variance, and standard deviation.
3  Describe the properties of the normal curve and standard scores.
4 & 8  Discuss measures of association appropriate for nominal, ordinal, interval and ratio data. 4 & 9 Compute and explain the meaning of Pearson’s correlation coefficient.
4 & 9  Compute and interpret the coefficient of determination.
5  Explain the concept of the sampling distribution of means.
5 & 6  Interpret the standard error of the mean.
5 & 6  Explain a probability distribution and its major use.
5  State the meaning and basic properties of probability.
5  Explain the importance of the Central Limit Theorem.
7  Define type I error, type II error, statistical power, and effect size.
5  Illustrate how to conduct a statistical test about a population mean based on a one-sample z test.
5  Illustrate how to conduct a test about a population mean based on a one-sample t test.
6  Illustrate how to test hypothesis involving mean differences between independent samples. 6 Illustrate how to test hypothesis involving means of dependent samples.
5  Explain the meaning of a null hypothesis and alternative hypothesis.
6  Determine the sample size needed for a study, given α, β, and effect size.
8  Demonstrate the utility of the Chi-square test of independence.
6 & 7  Distinguish between statistical and practical significance.
5 & 6  Distinguish between the test statistics and critical value.
4 & 9  Distinguish between the purposes of correlation and regression.
4 & 9  Perform a test of significance of a correlation coefficient.
9  Compute and interpret the elements in regression analysis.
9  List the null and alternative hypotheses in regression analysis.
7  Develop and interpret the source table in ANOVA.
7  List the null and alternative hypothesis generated in ANOVA.
7  Compute appropriate post hoc analyses in ANOVA.
7  Run SPSS for ANOVA and regression and discuss the results
7 & 9  Explain the assumptions of ANOVA and regression.
8  Differentiate between parametric and nonparametric tests.

HOMEWORK ASSIGNMENTS

Assignment Points Topic Due date
 1  10  Descriptive Statistics Feb 6
 2  10  Univariate Statistics 1 Feb 13
 3  10  Univariate Statistics 2 Feb 20
 4  10  Normal Distributions Feb 27
 5  10  Bivariate Distributions Mar 6
 6  10  Hypothesis Testing (z test;  t test) Mar 20
 7  10  Comparing the Means of 2 Groups Apr 3
 8  15  Research Paper, ANOVA Apr 17
 9  10  Regression and Prediction Apr 24
 10  5  Chi-Square Test May 1
Total 100    

Note. The assignments must be typewritten and double-spaced.

GUIDELINES FOR WRITTEN RESEARCH PAPER: ASSIGNMENT ≠ 8

Using the data set that will be provided by the instructor on November 15, perform the analysis of variance (ANOVA) statistical procedure and write a report. Your report should include the following sections:

  1. Introduction, including research questions, with hypotheses listed in words and symbols;
  2. Method, including population, sample, research design, and statistical method used for data analysis;
  3. Results, including descriptive statistics, inferential statistical analysis using a summary table; (SPSS outputs should be attached to the assignments); and
  4. Discussion, including summary and interpretation of the findings reported in the previous sections relative to the research questions you posed

The project must be typewritten, double spaced and very limited in length.

EVALUATIVE CRITERIA FOR THE RESEARCH PAPER

Clarity and focus  3 2 1 0
Relatedness to course objectives  3 2 1 0
Level of analysis (i.e. intensive summary)  3 2 1 0
Accuracy of interpretations  3 2 1 0
Validation of assumptions  3 2 1 0

 

 

 

 

3 = Adequate, 0 = Inadequate