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Course Title: Statistical Methods in Hospital Research
Course Code: HSPM 443
Credits: 3
Pre-requisite: None
Purpose:
- Provide students with an in-depth understanding of statistical concepts and methods applicable in social science research.

By the end of the course, students should be able to:

Understand Data Requirements:
- Recognize the data requirements for different types of statistical analysis.
Questionnaire Design Steps:
- Identify the steps involved in designing questionnaires for data collection.
Statistical Tests Understanding:
- Differentiate between parametric and non-parametric tests, including their equivalences.
Data Analysis in SPSS:
- Manipulate data and conduct data analysis using SPSS software.

Format of Instruction:
- Lectures
- Individual tasks including written and oral presentations
- Group works

Activities Covered:
- Formatting Word documents
- Designing a table of contents
- Page formatting
- Inserting and drawing shapes
- Utilizing basic functions of Microsoft Word
Venue: SH 7

Topics Covered:
- Descriptive statistics
- Parametric tests
- Non-parametric tests
- Other statistical techniques
Group Assignment:
Venue: SH 7

Activities Covered:
- Usage of Kobo toolbox
- Understanding variable view
- Analyzing data view
Assessment: Quiz 1
Venue: SH 7

Activities Covered:
- Data entry in Microsoft Excel
- Usage of basic Microsoft Excel functions
- Drawing graphs, charts, and histograms
Venue: SH 7

Topics Covered:
- Collapsing continuous variables into categories
- Transformation of data
- Computing variables
- Using the split function in SPSS

Topics Covered:
- Assessing data normality
- Understanding kurtosis and skewness
Assessment: Quiz 2
Venue: SH 7

Topics Covered:
- Spearman's rank order correlation
- Pearson's correlation
- Linear regression analysis
Venue: SH 7

Course Title: Statistical Methods in Hospital Research
Course Code: HSPM $443$
Credits: $3$
Pre-requisite: None
Purpose:
- Provide students with an in-depth understanding of statistical concepts and methods applicable in social science research, focusing on healthcare environments.

By the end of the course, students should be able to:

Understand Data Requirements:
- Recognize the data requirements (nominal, ordinal, interval, and ratio scales) for different types of statistical analysis.
Questionnaire Design Steps:
- Identify the steps involved in designing valid and reliable questionnaires, including pilot testing and ethical considerations.
Statistical Tests Understanding:
- Differentiate between parametric tests (which assume a normal distribution) and non-parametric tests (which are distribution-free).
Data Analysis in SPSS:
- Manipulate datasets and conduct complex data analysis using IBM SPSS software.

Format of Instruction:
- Interactive Lectures
- Individual tasks including written reports and oral presentations
- Collaborative group work and peer reviews

Activities Covered:
- Advanced formatting of Word documents (styles and themes)
- Designing an automated table of contents and list of figures
- Page formatting: margins, orientation, and section breaks
- Inserting and drawing shapes, SmartArt, and organizational charts
- Utilizing basic functions and keyboard shortcuts for efficiency
Venue: SH $7$

Topics Covered:
- Descriptive statistics: Measures of central tendency (Mean, Median, Mode) and measures of dispersion (Range, Variance, Standard Deviation).
- Parametric tests: Analysis involving the assumption of normality (e.g., Pearson correlation, t-tests).
- Non-parametric tests: Analysis for non-normal data or small sample sizes (e.g., Chi-square, Mann-Whitney U).
- Other statistical techniques: Understanding sampling frames and error margins.
Group Assignment: Data set exploration and initial descriptive reporting.
Venue: SH $7$

Activities Covered:
- Usage of Kobo Toolbox: Designing digital surveys for mobile data collection.
- Understanding Variable View: Defining variable names, types (numeric, string), labels, and missing value codes in SPSS.
- Analyzing Data View: Entering raw data and checking for entry errors.
Assessment: Quiz $1$ (Questionnaire design principles)
Venue: SH $7$

Activities Covered:
- Structural data entry and data cleaning in Excel sheets.
- Usage of functions: Applying mathematical formulas (e.g., $=SUM()$ , $=AVERAGE()$ , $=STDEV()$ ).
- Visualization: Creating dynamic graphs, pie charts, and frequency histograms to represent data distributions.
Venue: SH $7$

Topics Covered:
- Collapsing continuous variables: Re-coding continuous data (e.g., age) into categorical groups (e.g., age brackets).
- Transformation of data: Logarithmic transformations to address skewness.
- Computing variables: Creating new variables based on existing data via logic (e.g., calculating a total score from sub-items).
- Split Function: Analyzing groups separately within the same dataset.

Topics Covered:
- Assessing data normality: Utilizing the Shapiro-Wilk and Kolmogorov-Smirnov tests.
- Understanding Kurtosis and Skewness: Identifying the "peakedness" and symmetry of the distribution ( $Skewness = 0$ for perfect symmetry).
Assessment: Quiz $2$ (Interpreting normality outputs)
Venue: SH $7$

Topics Covered:
- Spearman's rank order correlation ( $\rho$ ): Non-parametric measure of monotonic relationships.
- Pearson's correlation ( $r$ ): Parametric measure of the linear relationship between two continuous variables ( $-1 \leq r \leq 1$ ).
- Linear regression analysis: Modeling the relationship between a dependent variable ( $y$ ) and an independent variable ( $x$ ) using the equation $$y = \beta_{0} + \