CNSL503/ CNSL 503 Module 1 Statistics 2026/2027 | Portage Learning | Verified Questions & Answers | 100% Correct | Grade A

CNSL503/ CNSL 503 Module 1 Statistics 2026/2027 | Portage Learning | Verified Questions & Answers | 100% Correct | Grade A Q: What are statistics? Answer Statistics encompass the mathematical field that allows us to organize, summarize, describe, and interpret different forms of information. Q: Name 3 reasons why statistics are important Answer 1. Statistics allow data to be described and communicated succinctly and concisely. 2. Statistics allow inferences to be drawn about data, particularly when it is not feasible to collect information from all members of a certain group. 3. Statistics equip us with the necessary tools needed to critically evaluate information. Q: Qualitative variables Answer Variables measured in non-numerical terms, using categories or labels Q: Quantitative variables Answer Variables measured in numerical terms Q: Discrete variables Answer Those that hold discrete values, such that they can be organized into separate categories or counted using whole numbers Q: Continuous variables Answer Variables that can theoretically be broken down into infinitely smaller, fractional components Q: Name at least 3 examples of qualitative variables Answer One's religion, ethnicity, eye color, and career Q: Name at least 3 examples of quantitative variables Answer Weight, height, heart rate, and test scores Q: Describe the important variables involved in an experimental study Answer The variable that is manipulated in an experiment is known as the independent variable, and the variable that is measured for any observable effect is known as the dependent variable. A control variable is a variable that remains unchanged throughout the experiment. Extraneous, or confounding, variables include any variables that could unintentionally affect the dependent variable. Q: Suppose you want to study the effects of a genetically modified diet on the weight of dogs. Answer Give at least 3 examples of extraneous variables. Q: Explain why the variables are extraneous. Why is important to identify extraneous variables in an experimental study? Answer 1. Activity level: Dogs given more space and opportunity for exercise may burn more calories, thus affecting the weight. 2. Genetics: Different breeds of dogs may be prone to gain weight at different weights. 3. Environment: Whether a dog is kept inside or outside may impact weight. Extraneous variables may have an effect on the dependent variable and could skew the results of the experiment. They may also lead the researcher to draw incorrect conclusions. Q: Why is it important that extraneous variables be taken into account in an experimental study? Answer Extraneous variables may have an effect on the dependent variable and could skew the results of an experiment. Q: What is an ordinal scale of measure Answer Used to describe qualitative variables, provide both categorical information as well as rank by size or measure Q: What is a nominal scale of measure Answer Used to describe qualitative variables, provides only categorical information Q: What is a ratio scale of measure Answer Used to describe quantitative variables wherein there exists an absolute zero (e.g. height and weight) Q: What is an interval scale of measure Answer Used to describe quantitative variables wherein an absolute or meaningful zero does not exist (e.g. temperature) Q: What is the relationship between a sample and a population? Answer A population includes every member within a particular group, whereas a sample is a smaller subset of a given population. Q: How do researchers use samples to make inferences about a population? Answer Many times, it is not possible to collect data from every member of a given population. Thus, researchers will collect data from samples of a larger population and use the findings from these samples to draw inferences about the population as a whole. Q: Define inferential statistics Answer Performed in order for researchers to make inferences and generalizations about populations based on data gathered from samples (e.g. calculations such as those used for hypothesis testing). Q: Define descriptive statistics Answer Involves analyses that provide a way to summarize and describe data (e.g. mean, median, mode). Q: Why is it important that statistical methods are performed ethically? Answer Statistics is a very powerful tool that allows large amounts of information to be communicated and understood concisely. However, if statistical methods or data collection are performed unethically or irresponsibly, it can skew the results of a study and very easily mislead others into believing claims that are not necessarily supported by evidence. Q: Why is it important to understand statistics and ethical conduct of statistical methods? Answer It is very important that we are equipped to critically evaluate claims that we encounter from any source each day so that we are able to make responsible decisions. By understanding the proper ways statistics can be used and the strengths and limitations of these techniques, we will be much better able to detect false or inaccurate claims and accept claims with adequate empirical support. Q: Statistics Answer Encompasses the mathematical field that allows us to organize, summarize, describe, and interpret different forms of information Q: Data (datum) Answer Small and large sets of information Q: What are statistics important? Answer 1) allows data to be described and communicated succinctly and concisely 2) means by which researchers communicate their work with one another and the general public, clear and understandable 3) allow inferences to be drawn about data, particularly when it is not feasible to collect info from all members of a certain group 4)equip us with the necessary tools needed to make everyday decisions Q: Variable Answer Measurable characteristics that can vary in value ex: job satisfaction, religion, cancer, temp, patients in hospital Two types of variables Answer qualitative and quantitative Qualitative variable Answer Non-numerical terms, using labels or categories (religion, ethnicity, eye color, career) Quantitative variable Answer Measured in numerical terms (weight, height, hr rate, test score) Two types of quantitative variables Answer discrete and continuous Discrete variable Answer quantitative variable that is organized by whole numbers (0,1,2,3...) (number of people, children, animals) continuous variable Answer has an infinite number of values between observations temp, time experiment Answer a specific research methodology aimed at examining cause and effect relationships independent variable Answer Variable that is manipulated in an experiment Cause Dependent variable Answer The variable that is measured for any observation effect Effect Control variable A variable that remains unchanged throughout the experiment pill color Extraneous variable a variable that the researcher is not intentionally studying that may influence the dependent variable ex smoking status confounding variable extraneous variable that can explain changes in the dependent variable instead of the independent variable undermine validity of experiment Qualitative variables are measured by Nominal or ordinal scales Nominal scale Means names Variables that provide categorical info Values are not ordered (blood type, college majors, room numbers) (not greater than or less than) Ordinal scale Means ordering Provides information about ranking by size or measure Does not provide information about magnitude or differences between values ex: runner placement in marathon, shirt sizes Quantitative Variables are measured by Ratio or interval scales Ratio scale contains ordered values that are the same distance apart There exists an absolute zero, 0 has a meaning Ex: cups of coffee, height, weight, number of errors no negative values! Interval scale contains ordered values that are the same distance apart no absolute 0 ex: temp on fahrenheit scale Scales of Measurement nominal, ordinal, interval, ratio sample Smaller subset of a group being studied descriptive statistics Involves analyses that provide a way to summarize and describe data. Descriptive stats involve calculations such as the mean, median, mode, standard deviation, variance and range of a set of scores Population Includes every every member within a particular group being studied ex: everyone diagnosed w/ depression, voters Inferential statistics Are performed for researchers to make inferences and generalizations about populations based on data gathered from samples. Calculations used for hypothesis testing (z-score, t-tests, ANOVA, and correlation all analyses) Ethical use of statistics 1) to communicate large amounts of information in a clear and simplified manner 2) serve as a means of drawing inferences Ana's forming conclusions about relationships between different variables. 3) provide evidence to support claims or to frame an argument Importance of ethical handling of data Applies to data collection, analysis and interpretation. Improper data collection can result in Biased and skewed results Incorrect analysis can lead to False conclusions Regarding the interpretation of statistical results, researchers mush understand the Strengths and limitations, that characterize each statistical method and responsible for the claims they make about the statistics they obtain Quantitative variables are measured by Ratio or interval scales Continuous variable Quantitative variable, can be broken down into infinitely smaller, fractional components (Temp, time, length, speed) Correlational Study examines relations between variables but does not provide cause and effect