Homework 1 Behavioral Statistics

HOMEWORK 1 1. What is the difference between descriptive and inferential statistics? Use examples for each in your answer. Descriptive statistics is using data to describe something we do know, like using a thermostat to describe the current temperature. While inferential statistics uses data to make inferences of something we do not know, like when we predict the future temperature of the week. 2. Indicate the scale (level) of measurement (nominal, ordinal, interval, or ratio) used in each of the following scenarios. a. The finishing places of one competitor during the 2018-2019 season of the Women’s Downhill Skiing tournament. ORDINAL b. The SAT scores for each student in the graduating class at Central High School. NOMINAL c. The weight in pounds of every adult male insured by Metropolitan Health Insurance. RATIO d. The zip codes of every person with the last name Hanks. NOMINAL e. The numbers of all the roads (e.g., Highway 41) in the state of Virginia. NOMINAL f. The academic status (sophomore, junior, etc…) of all the students enrolled in social psychology classes at the University of Maryland College Park. ORDINAL g. The aggression scores (on a scale from –100 to +100) of a sample of police personnel. RATIO h. The average annual temperatures in Celsius of all the counties in Maryland. INTERVAL 3. Provide brief hypothetical examples of a correlational research study and an experimental research study. An example of a correlational research study would be if there were three ice cream trucks, each with a different jingle, and we memorized each jingle in relation to its truck. This is correlational because one variable does not cause the other, they are related and the variables are being measured, not manipulated. An example of an experimental research study would be having two randomly selected study groups, giving one a placebo pill and the other a pill that does nothing, but not telling them which. There is a variable being manipulated here as well as random assignment in place. 4. For the following two examples, indicate the independent variable, the dependent variable, and one potential confounding variable. a. An instructor wants to determine whether the color of the paper on which an exam is typed influences a student's performance. She randomly selects half of a statistics class to take an exam in one room with blue paper and the other to take an exam in another room with white paper. The average exam scores for the two groups are then computed and compared. Independent variable: the color of the paper Dependent variable: both groups have students from the same class taking the exam Confounding variable: the exam content and how the environment/room their in affects them b. A nurse wants to empirically test the old adage “starve a cold”. As people enter her clinic, those that are diagnosed with the common cold are randomly divided into three groups. One third of the patients are fed 150% of the normal dietary intake, one third are fed 100% of the normal dietary intake, and one third are fed 50% of the normal dietary intake. 36 hours later, all patients are assessed again to determine whether their symptoms have improved or deteriorated. Independent variable: what percentage of normal dietary intake patients are being fed Dependent variable: the amount of time Confounding variable: how the subjects immune systems previously were (chronically ill or possibly old)