W1&2 Stats Lecture Notes PDF

Audio Name: W1&2 stats\ Duration: 143.52 [[Click here to provide feedback]](https://messengerpigeon.habitatlearn.com/feedback?session=bff16767-77e2-4b3a-b5c5-cec70daec0bd&recording=W1&2%20stats) **[ANNOUNCEMENTS]** **Reminder** - The first test will be in week four. - Tests will cov...

Audio Name: W1&2 stats\ Duration: 143.52 [[Click here to provide feedback]](https://messengerpigeon.habitatlearn.com/feedback?session=bff16767-77e2-4b3a-b5c5-cec70daec0bd&recording=W1&2%20stats) **[ANNOUNCEMENTS]** **Reminder** - The first test will be in week four. - Tests will cover material from the first three weeks. - Students with accommodations should book appointments with the distance center early. - Assignments - Collaborative work is encouraged. - Apply what is learned in class to assignments. - Lab work includes wound care, injections, and potentially catheters. **[LECTURE]** **Prevalence and Policy Development** - Prevalence - The number of people with a specific health condition, such as hypertension. - Application - Use data on prevalence to develop policies.  - Example - If assessing the prevalence of hypertension in Ontario, use this data to advocate for funding and create effective health policies. - Resource Management - To gain funding or support, present data from research.  - Demonstrate the need and potential impact of your proposal. **Research and Data Collection** - Research - Research to understand and address health issues.  - Example - Analyze data on patient satisfaction and quality of life. - Sample - A set of observations from a larger population.  - Samples are used to make inferences about the population. - Data Types - Descriptive Statistics - Describe data without analyzing relationships. - Example - Reporting on the average age of patients. - Inferential Statistics - Analyze data to make predictions or generalizations. - Example - Comparing stress levels between two experimental groups to evaluate an intervention. **Types of Data Measurement** - Nominal - Categorizes data without a specific order. - Example - Types of diseases. - Ordinal - Categorizes data with a specific order. - Example - Severity levels of a condition. - Interval - Measures data with equal intervals but no absolute zero. - Example - Temperature - Ratio - Measures data with equal intervals and an absolute zero. - Example - Weight **Data Analysis Techniques** - Descriptive Analysis - Provides an overview of data by describing its main features without making further inferences. - Inferential Analysis - Uses sample data to make generalizations about a population. - Comparison - Use experimental and control groups to assess the effect of interventions. - Accuracy - Ensure calculations and measurements are accurate.  - Example - Verify that multiplications in calculations are correct. - Presentation - Make sure that the final report is clear and concise.  - If handwriting is involved, legibility is crucial. - Data Interpretation - Understand the difference between interval and ratio scales to accurately interpret results.  - Interval scales lack an absolute zero, while ratio scales include it. - Example - If measuring the impact of a health intervention over several years, track variables yearly and compare results. - Interval Data - For temperature, note that zero does not imply the absence of temperature but a low level. - Simplify - When presenting data or findings, simplify complex concepts for clarity. - Verification - Double-check calculations and interpretations to ensure accuracy. - Printing and Submission - There was confusion about whether the document should be printed or submitted electronically. - It\'s preferred to fix and submit the document electronically. - Pain Categories - Moderate Pain vs. Severe Pain - Difficulty distinguishing between different levels within these categories. - Comparisons between individuals within each category may be unclear. - Statistical Concepts - Nonparametric Statistics - Used for analyzing nominal data or examining relationships among variables. - Applied when data is not normally distributed, and may also be used with interval and ratio data in such cases. - Parametric Statistics - Assumes data is normally distributed. - Suitable for interval or ratio data. - Includes calculating mean and median, though mean may be affected by outliers in non-normally distributed data. - Types of Measurement - Nominal Data - Described using frequencies and categories. - Ordinal Data - Ranked in order but not quantified. - Interval Data - Measures differences between values, but no true zero. - Ratio Data - Includes a true zero and allows for a wide range of statistical operations. - Use of Median and Mean - The median is preferred over the mean for non-normally distributed data. - The mean can be misleading if the data distribution is skewed or contains outliers. **Seasonal Challenges** - Winter Struggles - The difficulties with nerve and bone pain in winter, are exacerbated by lack of daylight. - Anticipation for the summer to alleviate these issues and improve overall well-being. **Technology and Research** - Apple Pen - The use of a new Apple Pen with convenient charging. - Research and Data Analysis - Analyzing patient demographic and clinical characteristics. - How to interpret numbers and variables in research data, focusing on heart failure types and current therapies. - Measurement levels for current therapy variables and their implications in research data. **Sample Description and Data Analysis** - Sample Size - The total number of participants is 106. - The final sample size for analysis is 100. - Demographics and Clinical Characteristics - Age - Mean age - 64 years - Standard deviation - ±12 years - Sex - Percentage of females - 19% (19 out of 100 participants) - Current Therapy - Aldosterone and Therapy - Participants may be using multiple therapies; the total number may not sum to 100 as participants may use more than one therapy. - Descriptive Statistics - Mode - The mode is the most frequently occurring value. - Body Mass Index (BMI) - Mean BMI - Specific value not provided; typically reported with mean ± standard deviation. - Frequency and Severity - Total Number of Clients with Stable Conditions - Specific numbers and categories not detailed. - Severity of Disease - Variations exist even within the same stage; categories may not reflect exact differences between clients. - Depression Measurement - Total Score - Mean depression score: 86 - Percentage of clients with depression: 36% - Measurement Levels - Scores may range from 0 to a higher number, reflecting varying levels of depression. - Ratio scale if actual zero represents no depression; otherwise, it may be treated as an interval scale. - NYHA Class and Depression - Relationship between NYHA class and depression not quantified in detail. - No specific numbers provided regarding differences between classes. - The results include mean scores and percentages without detailed breakdowns for all categories. - Specific questions and answers related to the study were mentioned, including potential issues with data reporting.