Overview
1.
Fill in the blanks below. Please note that spelling matters!
categorical, data, decimal, descriptive, fraction, inferential, mean, numerical, parameter, percentage, population, probability, sample, statistic, variable
Question at position 1
A ...........is a characteristic of a group that varies from individual to individual. These can be .........., meaning there are different groups individuals may be part of (like gender, or what color something is). They can also be ........, meaning they can be measured or counted (like distance in inches or number of siblings someone has).
Question at position 2
I have one cat that weighs 6 pounds, one that weighs 7 pounds, one that weighs 8 pounds, and one that weighs 11 pounds. I can calculate their.......weight (also called an average) by adding their weights (6 + 7 + 8 + 11 = 32) then dividing by the number of cats (32 / 4 = 8).
Question at position 3
There are two different major categories of statistics: descriptive and inferential. You can use........statistics to organize and provide a summary of ...........either by graphing it or calculating summary numbers. The type of statistics that we use to draw conclusions about the populations our data come from are.......... statistics.
Question at position 4
When describing how statistically likely something is to happen, we refer to that likelihood as...........
and can write it in several different forms. For example, if a bag of Starbursts with 20 pieces of candy in it has 5 strawberry ones, we could write this likelihood as a...
such as 5/20 or 1/4, as a .............such as 25%, or as a ..........such as 0.25.
Question at position 5
Often, we want to answer questions about a........., or entire existing group of people or objects. However, we almost never have the ability to get data from every individual in the group. Instead we gather data from a ........., or smaller representative group. If we then use that data to calculate something like an average for the smaller representative group, that is referred to as a........... If we're talking instead about the average or another numerical characteristic for the entire larger group, that is called a ............
2.
A.
There are two levels of measurement typically associated with quantitative data.
The difference between them is that data measured on a(n) __________ scale has a meaningful 0 point (in other words, 0 truly means "none"), but data measured on a(n) __________ scale does NOT have a meaningful 0 point.
interval; ratio
ratio; interval
ordinal; nominal
nominal; ordinal
B.
On a survey, participants were asked how many pets they owned. What kind of variable is this, and what kind of data would the answers provide?
categorical variable, qualitative data
numerical variable, qualitative data
categorical variable, quantitative continuous variable
numerical variable, quantitative discrete data
categorical variable, quantitative discrete data
numerical variable, quantitative continuous data
C.
To study public opinion on a new law, a public policy company emailed all the people on their listserv. They asked them to provide their opinions on a survey, and used the responses of whoever answered within the first week. What kind of sampling strategy was used?
stratified sampling
convenience sampling
cluster sampling
simple random sampling
systematic sampling
D.
There are two levels of measurement typically associated with qualitative data.
The difference between them is that data measured on a(n) __________ scale have a natural order to them, but data measured on a(n) __________ scale do NOT have a natural order.
Which two words correctly fill in the blanks?
There are two levels of measurement typically associated with qualitative data.
interval; ratio
ratio; interval
ordinal; nominal
nominal; ordinal
E.
To study employee satisfaction with working conditions in their company, a large chain store randomly selected 10 of their 100 stores. They then surveyed every employee in each of those 10 stores. What kind of sampling strategy was used?
To study employee satisfaction with working conditions in their company, a large chain store randomly selected 10 of their 100 stores. They then surveyed every employee in each of those 10 stores. What kind of sampling strategy was used?
stratified sampling
systematic sampling
convenience sampling
simple random sampling
cluster sampling
F.
On a survey, participants were asked to describe themselves using their three most salient social identities (such as ethnicity, religion, career, etc.). What kind of variable is this, and what kind of data would the answers provide?
categorical variable, quantitative discrete data
numerical variable, qualitative data
categorical variable, qualitative data
numerical variable, quantitative discrete data
numerical variable, quantitative continuous data
categorical variable, quantitative continuous variable
G.
In a lab, a scientist was measuring the exact weight of specimens of toad to the nearest hundredth of a milligram. Which is the best description for the type of data and level of measurement?
quantitative discrete data, ratio measurement
quantitative continuous data, interval measurement
quantitative discrete data, interval measurement
quantitative continuous data, ratio measurement
H.
A scientist wanted to study the population of all babies born in Los Angeles hospitals in the year 2020. The scientist used hospital records to create a complete list of that population, numbered them, then used a random number generator to choose 100 babies as her sample. What kind of sampling strategy was used?
convenience sampling
systematic sampling
cluster sampling
simple random sampling
stratified sampling
I.
To study the impact of a new school policy on LAHC students, administrators made a list of all current LAHC students and put them in order by student ID. They then used a random number generator to choose where to start on the list. Starting at that point, they surveyed every 20th student. What kind of sampling strategy was used?
stratified sampling
simple random sampling
systematic sampling
cluster sampling
convenience sampling
J.
Match each of the following examples with the correct level of measurement. Each option is used once.
nominal, interval, ratio, ordinal
"What is your top hobby?"
"How many minutes of sleep did you get?"
"What is the highest educational degree (e.g., HS diploma, AA, BA, Master's) that you have earned?"
"Using military time (00:00 to 23:59) for your response, what time did you wake up this morning?"
K
Match each of the following descriptions with the correct level of measurement. Each option is used once.
nominal, interval, ratio, ordinal
Data values at this measurement level are categories that can be put in order, and sometimes they look like numerical data (but aren't really
Data values at this measurement level have equal distances between units, and a 0 truly means that there's nothing of whatever you're measuring
Data values at this measurement level can be put in order, and the distance between units of measurement is the same
Data values at this measurement level are only in the forms of names of categories
3.
This discussion is meant to give you some practice thinking through the idea of hypothesis testing. Your job for this post: choose two variables that you think would be related to each other, write a research question and alternative and null hypotheses about the variables, and explain why you expect the alternative hypothesis to be true. Note that the hypotheses should be directional hypotheses (details below).
A. (3 pts) Write Alternate and Null Hypotheses
Write a directional, alternative hypothesis showing how you think the two variables would most likely be related.
Make sure you are specific about the way you think the two variables would be related to each other.
Write a null hypothesis about your two variables
Make sure that you include the variables having no relationship
Make sure that you include the opposite-direction relationship to the one you state in your alternative hypothesis
B. (2 pts) Explain your Reasoning
Explain why you think that your alternative hypothesis would be true. You do not have to provide scientific citations or calculations; we're only practicing hypotheses and not the entire hypothesis-testing process. Just explain the real-life observations or thought processes that lead you to believe your alternative hypothesis would be accurate.
C. (2 pts)
State a different alternative hypothesis variable, and explain your reasoning. Explain why you agree with expected outcome.