explain additional analyses that could be done with the variables selected. Consider confounding variables, discrete or continuous data, the effects of outliers. etc

Types of Data: Gender and Weight 1. Gender- Qualitative data as gender describes/ or labels a population and it is a non-numerical entry. An attribute that one possesses in which the researcher is sampling 2. Level of measurement: Nominal: Qualitative data only Uses labels or names - Gender has 2 categories . No mathematic computations can be made with this data 3. Type of sampling: Stratified sampling - The population is divided into subgroups (strata) based on specific characteristics such as gender . Within the strata random sampling is used to choose the sample 4. Advantages and Disadvantages: Advantages: . Strata cab be proportionally represented in the final sample It is easy to easy to compare subgroups - Disadvantages: Information must be gathered before being able to divide the population into subgroups - Weight- Quantitative data as weight is a numerical measurement and has a numerical meaning - Level of measurement: Ratio: The scale for weight in pounds starts at zero pounds. - There is an inherent zero; an absence of value Type of sampling: Simple random sampling Obtaining a patient's weight in a doctor's office - Advantages and Disadvantages: - Advantages: . Participants have an equal and fair chance of being selected . This technique also provides randomized results from a larger pool such as from hospital admissions - Disadvantages: . Success relies on population count (Low admission rate) - Patterns can be predicted (Specialty of doctor's office (Peds, Cardiologist, respiratory MD office) References: Chamberlain University. (2021). MATH225N-16557 Week 1: Lesson | Introduction to Statistics: Data Collection and Data