Project 1: America’s Top High Schools 2016

Statistics is the science of collecting, organizing, summarizing and analyzing information in order to draw conclusions or answer questions.

In this project, you will use the America’s Top High Schools for 2016 data set to answer the following questions. Your assignment is due to the iCollege Dropbox on February 7(TTh classes) or February 8(MW classes) at 11:59 pm. Make sure that EVERYONE in the group proofreads the project BEFORE submission. There will be a 10 point deduction PER DAY if the assignment is submitted late. If you are absent from class, you will have to complete this project individually, and the late point deduction will still apply. Make sure to round all decimals to the hundredths place. All interpretations should come directly from the lecture notes.

Circle your class day and time: MW 7 amMW 8:30 amTTh 7 amTTh 8:30 am

Group Number:______

List all group members who participated in completing this project: ______

Point Value / Points Earned / Requirement
2 /
  1. Considering all high schools in the U.S., would this list be considered a population or a sample?

2 /
  1. For the variable State, identify whether this is a qualitative or quantitative variable.

2 /
  1. For the variable College Bound, is this a discrete or continuous variable?

4 /
  1. Using Poverty, x(explanatory variable) and College Readiness, y, (the response variable), list at least three potential lurking variables.

4 /
  1. Can you say that the level of Poverty causes the level of College Readiness? Explain why it could or could not.

3 /
  1. Using a graphing calculator with a seed set to 53, create a simple random sample of size 10. List the corresponding rank and School Name. Make sure to use sampling without replacement.

3 /
  1. Create a relative frequency distribution of the states.

3 /
  1. Create a bar graph of frequency of the states. Make sure to include a chart title and axis titles.

3 /
  1. Create a pie chart of states in which the top high schools are located. Make sure to include a chart title.

3 /
  1. Create a frequency distribution for the graduation rate with the first lower class limit of 0 and a class width of 40.

3 /
  1. Create a frequency histogram based on the previous problem. Make sure to include a chart title and axis titles.

2 /
  1. Calculate the mean Graduation Rate.

2 /
  1. What is the median for the Poverty Rate?

4 /
  1. What is the mode for the State variable? What does/could this value tell you about this(these) state(s)? *Do not define what mode is.*

2 /
  1. Calculate the range of the College Readiness score.

2 /
  1. Calculate the standard deviation of the College Bound score.

3 /
  1. Determine the z-score of a school whose Poverty Rate is 2.2.

2 /
  1. Interpret what your z-score in Part 17 means.

3 /
  1. Identify the 5-number summary of the Graduation Rate.

4 /
  1. Are there any outliers for the Poverty Rate? If yes, how many are there and what are they? List the names of the schools and the corresponding value.

3 /
  1. Create a box-and-whisker plot of Poverty Rate. Make sure to include a title and appropriate axis title.

2 /
  1. Create a scatter diagram of Poverty, x (the explanatory variable) and College Readiness, y, (the response variable). Make sure to include a chart title and axis titles.

2 /
  1. Using Poverty, x (the explanatory variable) and College Readiness, y, (the response variable), calculate the linear correlation coefficient. Round your answer to the nearest hundredth.

4 /
  1. Explain what your linear correlation coefficient tells you, and make sure to relate it to Poverty and College Readiness.

3 /
  1. Using the Table of Critical Values for Pearson Correlation with atwo-tailed probability of 0.05, determine whether a linear relationship exists between Poverty and College Readiness.Explain your results.

2 /
  1. Regardless of whether a linear relationship exists, write the equation for the least-squares regression line that relates Poverty, x (the explanatory variable), and College Readiness, y (the response variable).

2 /
  1. Use the least-squares regression line to predict the College Readiness if the Poverty rate is 55.3.

4 /
  1. Would it be a good idea to use this model to predict the College Readiness whose Poverty rate is 90? Explain why it would or would not.

2 /
  1. Calculate the slope of your least-squares regression line.

3 /
  1. Interpret the slope.

2 /
  1. Calculate the y-intercept of your least-squares regression line.

3 /
  1. Interpret the y-intercept.

2 /
  1. Calculate the coefficient of determination.

3 /
  1. Interpret the coefficient of determination.

7 /
  1. Research: The College Bound variable has a few data values missing. Research two different ways that missing values are handled when cleaning data. Write 1 – 2 paragraphs about what you learned. Make sure to include a list of sources used formatted according to APA 6th edition.

0-10 /
  1. Optional: What additional insights do you have about this data set?
(This question allows you to give thoughts about this data set. Here are questions to start you to think about this assignment and what you can research and analyze.)
Did you learn anything? Did anything surprise you? Did their methodology make sense? Do you think they should have included any other criteria? Did any schools stand out in particular? Does this data sway you to want to move somewhere else so that your children/siblings have a better opportunity? Let your data analysis and critical thinking skills shine through here!
This question gives you the opportunity to act and think like a Data Analyst/Data Miner. The data is here, but you have to dive into it to see patterns, trends, oddities, etc.
DEDUCTIONS:
-10 / There will be a deduction of ten points if there are more than five errors in grammar, usage, punctuation, or spelling.
You have MS Word spell check, Grammarly, the Learning and Tutoring Center, and five other team members.
-10 per day / There will be a ten point deduction per day that the project is submitted late.
Project Total (Max is 100)