Statistics - Module 4 (Questions and Answers A+ Graded 100% Verified)

Statistics - Module 4 (Questions and Answers A+ Graded 100% Verified) Data Ans: are factual information, especially information organized for analysis or used to make decisions. Discrete data Ans: count(e.g., the number of patients on a ventilator, the number of patients with central lines) Continuous data Ans: measure(e.g., rate of surgical site infections among patients undergoing colorectal surgical procedures) data set Ans: is a group of observations whose individual values are connected in some way and are demonstrated in an array variable Ans: an observable characteristic of a phenomenon that can be measured—a quality, property, or characteristic of the person or things being studied that can be quantitatively measured or enumerated (e.g., age, sex, underlying disease, infections). dependent variable Ans: this variable is influenced or caused by another variable independent variable Ans: this variable influences or causes the dependent variable (e.g., ventilator, indwelling urinary catheter). Statistics Ans: involves collecting, organizing, and analyzing data and drawing conclusions on the meaning of the data. • Aids in organizing and summarizing data. • To communicate findings clearly and meaningfully to others. • To make inferences about data. Cannot prove either an association or causality; it can merely suggest that an association exists. The strength of the association between cause and effect is determined by computing statistical tests The IP will need some basic statistical skills to: Ans: • Describe an outbreak (mean, attack rate, possibly standard deviation). • Select control subjects who are similar to case subjects in regard to possible exposure. • Identify the distribution of the data (normal, skewed, or unknown) in order to select the appropriate test to determine statistical significance. • Generate test hypotheses to establish statistical significance of an exposure or increase/decrease in rates. • Determine the correct graphic display based on type of data (discrete versus continuous). Some commonly used statistical methods: Ans: • Numeric summaries that describe characteristics of the population being studied (e.g., mean, average number of days of catheterization before development of a urinary tract infection) • Frequency distributions displayed as tables, graphs, or charts • Infection rates Types of statistics Ans: 1) Descriptive statistics 2) Inferential statistics Descriptive statistics Ans: Statistics that provide numerical information about variables. In simple terms, it uses numbers to describe characteristics of a data set. Types of descriptive statistics Ans: 1) Discrete data 2) Continuous data Discrete data Ans: data that contains whole numbers and are mutually exclusive (e.g., infected or not infected, male or female, blood type). Continuous data Ans: data that require the process of measuring, rather than counting data. Contains information that can be measured on a continuum or scale and can have numeric values between the minimum and maximum value (e.g., age; serum cholesterol level; temperature; infection rates). Continuous Inferential statistics Ans: make an assumption about a population based on a sample or calculates strength of association between cause and effect. Descriptive Statistics- Scales of Measurement Nominal Scale Ans: The nominal scale is the simplest or crudest level of measurement. Categories are used to classify observations into mutually exclusive groups or classes. No order is implied among the classifications. These observations are known as nominal data Descriptive Statistics- Scales of Measurement Ordinal Scale Ans: If observations are ranked so that each category is distinct and stands in some definite relationship to each of the other categories, the observations are known as ordinal data Descriptive Statistics- Scales of Measurement Interval Scales Ans: When data meet all the requirements for ordinal data and the exact distance between any two observations on the scale is known, they are called interval data. Frequency Measures Measures of Central Tendency Ans: Measures of central tendency describe how observations cluster around a middle value and locate only the center of a distribution measure. The methods include mean, median, and mode. mean(average) Ans: The most commonly used parameter. Symbols used include μ for population mean and x-bar (x) for sample mean. The formula to calculate the sample mean is: Median Ans: is the point at which 50 percent of the values fall below a middle value and 50 percent of values occur above the middle value. Mode Ans: represents the observation(s) that occur(s) most frequently in a data set and determines the height and shape of a curve. Data sets may have more than one mode and can be bimodal or multimodal. Small data sets may be nonmodal (e.g., there are no repeated values). The mode is most useful for describing qualitative data (used for nominal data and bimodal distributions). It is the least stable of the three measures of central tendency.