Week-4-Probability-and-Chance+%281%29
Page 1: Introduction to Week 4
Topic: Probability and Chance
Meeting Time: 11 AM
Page 2: Objectives
Review answers for Quiz 1
Administer Quiz 2
Break for refreshments
Practical session on Respondus and troubleshooting before the midterm exam
Page 3: Understanding Probability
Definition of Probability: Likelihood of an event occurring
Scale: Ranges from 0% (impossible) to 100% (certain)
Page 4: Normal Distribution
Characteristics: Mean, median, and mode are equal
Properties: Symmetrical shape
Real-World Relevance: Although theoretical, normal distribution often appears in nature
Page 5: Standard Deviation and Probability
Key Point: Total probability equals 100%
Significance: In normal distribution, can estimate probability of finding values by referencing standard deviation
Reference Link: Standard Deviation
Page 6: Application Example
Context: Sample of heights from 20 nursing students at UBCO
Objective: Estimate probability of selecting an individual with a height of 168 cm
Page 7: Sample Statistics
Sample Mean Height: 165 cm
Standard Deviation (SD): 5 cm
Probability Values: Key percentages for height ranges (34.1% for within 1 SD, etc.)
Page 8: Probable Height Range
Conclusion: 95% likelihood individual heights fall between 155 cm and 175 cm
Note on Standard Deviations: 2 SDs (10 cm on either side of the mean)
Page 9: Standard Deviation vs. Standard Error
Standard Deviation: Measures variability of sample observations
Standard Error: Indicates how close sample mean is to the true population mean
Interpretation: Smaller standard error suggests greater precision
Page 10: Expanding to Population Estimates
New context: Using same sample to estimate true population mean
True Population Mean: 167 cm
Page 11: Probability of Population Mean Range
Confidence Level: 68% probability for population mean between 163.2 and 166.8 cm
Note: 1 standard error on either side is limited
Page 12: Broader Confidence Interval
Confidence Level: 95% probability for population mean between 161.4 and 168.6 cm
Importance of Standard Error: Critical for calculating confidence intervals
Page 13: Understanding 95% Confidence Interval
Example Calculation: CI of 165 cm (161.4-168.6 cm)
Trust Level: Tight CI indicates more confidence in population mean estimate
Page 14: Discussion Time
Invitation for questions regarding the material presented
Page 15: Skewed Distribution Analysis
Conclusion: Inferences can still be made about population mean with adequate sample size
Example: Positively skewed distribution danych
Page 16: Frequency Distribution
Visual Representation: Sample individual distributions
Page 17: Probability Distribution
Illustrative Context: Comparison between population and sample distributions
Page 18: Sample Size and Distribution Requirements
Requirement: Sample must be large (>20) or normally distributed and randomly sampled
Confidence Metric: 95% of the time, true population mean lies within 2 standard errors
Page 19: Introduction to Hypothesis Testing
Definition: Inferential research with implications on populations
Importance of testable ideas: Identifying relationships between variables
Page 20: Statistical Significance
Definition: Probability indicating differences not due to chance
Common Significance Level: Typically set at 0.05 or 5% risk
Page 21: Understanding P-Value
Definition: Probability of observed outcome given null hypothesis is true
Implication of p<0.05: Less than 5% chance results are random
Page 22: Null Hypothesis Explanation
Definition: Represents no association (H0)
Practice: You never "accept" the null, only "fail to reject" it
Page 23: Alternative Hypothesis Overview
Definition: Represents existence of an association or effect
Note: You "reject" the null when evidence strongly suggests it is false
Page 24: Example Hypothesis Study
Null Hypothesis (H0): No significant difference in pain management outcomes for post-surgical patients with or without a multidisciplinary team
Alternative Hypothesis (HA): Significant improvement in outcomes exists with such an approach
Page 25: MBSR Techniques Study Example
Null Hypothesis (H0): No significant difference in stress levels between nursing students who undergo MBSR training and those who do not
Alternative Hypothesis (HA): MBSR training significantly reduces stress and improves coping skills
Page 26: Understanding Probability Samples
Characteristics: Probability of selection is known
Sampling Types: Simple Random Sample, Systematic, Stratified, Cluster
Page 27: Non-Probability Samples Explained
Characteristics: Probability of selection is unknown
Types: Convenience sampling and quota sampling
Page 28: Reasons for Non-Probability Sampling
Use case: Non-probability sampling is acceptable when you do not intend to extrapolate results to a larger population
Page 29: Review of Study on Emergency Department Visits
Background: Evaluation of changes in emergency department visits during the COVID-19 pandemic
Results Summary: Quantitative evidence on changes across demographics and reasons for visits
Page 30: Important Reminders
No Class Next Week (TRC)
Midterm Details: Online exam scheduled for October 7, begins at 11:30 AM with a 60-minute duration
Respondus Restrictions: No digital notes allowed, but physical cheat sheets permitted
Upcoming Office Hours: Posted on Canvas for pre-midterm consultation.