Comparing May Temperatures in Miami and Reykjavík

Posted on | by Linus

Student Learning Outcomes:
Graph and interpret paired data sets using scatter plots and time series charts.
Find measures of central tendency.
Find the range, variance, and standard deviation of a data set.
Solve applications involving confidence intervals for population means.
Overview: For this Project, you will be collecting and analyzing data on the daily high temperatures during the month of May, 2022 for Miami, FL and Reykjavík, Iceland. You will use this information to compare the two cities and make inferences on the true average high temperature during the month of May for these cities.
Please open and read through this entire document first: Midterm BONUS Project Instructions
Please see this Midterm Project Sample for an idea of what I’m looking for with this.
Note: This sample project is meant to help you out, but you should not copy it word for word and should instead try to write things up in your own words. Some portions will sound very similar to what I have, but you need to make sure you are really looking at YOUR data and what IT shows/says, not simply copying what I have provided here.
NOTE: Make sure you include (or separately upload) your dataset. There is an automatic 5pt penalty built into the rubric for not including your dataset.

 

Struggling with where to start this assignment? Follow this guide to tackle your assignment easily!

Step 1: Collect Your Data

  • Gather daily high temperatures for Miami, FL, and Reykjavík, Iceland for May 2022.

  • Organize your data in a spreadsheet with columns for Date, Miami Temp, and Reykjavík Temp.

  • Double-check that your data is complete and accurate to avoid errors in analysis.

Step 2: Graph Your Data

  • Create scatter plots to visualize the relationship between Miami and Reykjavík temperatures.

  • Create time series charts for each city to see how temperatures change day by day.

  • Label your axes clearly and give each graph a descriptive title.

Step 3: Calculate Measures of Central Tendency

  • Find the mean, median, and mode for both cities’ daily high temperatures.

  • Compare the two cities based on these measures to get an initial sense of trends.

Step 4: Calculate Measures of Variability

  • Compute the range, variance, and standard deviation for each city’s temperatures.

  • Discuss which city has more consistent temperatures during May and why.

Step 5: Apply Confidence Intervals

  • Use your sample data to calculate confidence intervals for the population mean high temperatures for both cities.

  • Interpret your results: What does the interval tell you about expected temperatures for May?

Step 6: Analyze and Compare

  • Compare the central tendencies, variability, and confidence intervals between Miami and Reykjavík.

  • Discuss why the temperatures differ, considering geographic and climatic factors.

  • Draw conclusions about what your analysis suggests for the true average high temperatures.

Step 7: Write Up Your Findings

  • Include Introduction: explain your purpose and dataset.

  • Include Methods: describe how you collected and analyzed data.

  • Include Results: graphs, tables, calculations, and confidence intervals.

  • Include Discussion/Conclusion: interpret your findings and compare the two cities.

Step 8: Include Your Dataset

  • Upload your dataset as required.

  • Ensure it matches your analysis exactly; missing or mismatched data will cost points.

Step 9: Review and Edit

  • Check that all calculations are correct.

  • Make sure your graphs are clear and labeled.

  • Proofread your write-up for clarity and logical flow.

Step 10: Helpful Resources

 

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