To complete this lab, answer the five questions below. Include graphs when required, with correct placement of x– and y-variables, axis labels, and legends.
Questions
- Calculate summary statistics for each of the following datasets (sample size, mean, median, standard deviation, and standard error). Round your answers to two decimal places.
- Set 1 = {7, 12, 5, 9, 4, 15, 9, 2, 8, 8, 6, 10}
- Set 2 = {23.5, 48.1, 6.2, 31.4, 17.6, 34.0, 29.3, 27.8, 25.5, 11.9}
- Set 3 = {53.11, 47.62, 101.06, 54.95, 46.27, 59.73, 52.82}
- Set 4 = {105, 311, 507, 389, 271, 356, 247, 1018, 251, 402, 343, 345}
- Set 5 = {0.11, 0.43, 0.37, 0.08, 0.25, 0.34, 0.17, 0.20, 0.14}
- In the Module 1 Resource Book, we performed a linear regression of the age and weight of ladybugs. In that example, we only had five data points (for ladybugs that were 2, 4, 6, 8, and 10 days old). I actually found 7 more ladybugs, so I want to add them to our dataset (combining everything we have) and redo the analysis. Both the original and new data are attached to this page as “02 Ladybug age-weight data” and “02 Ladybug age-weight data – new data”.
- Make an updated graph showing the age/weight relationship for all 12 ladybugs.
- Report the updated equation of the line.
- Report the new R2 value.
- Calculate the expected age for a ladybug that weighs 32 g. Show your work.
- Predict the weight of a 4.5-day-old ladybug. Show your work.
- On warm summer nights, you can tell the temperature by how fast crickets are chirping! The attached dataset “03 Cricket time-temperature data” is from Bessey & Bessey (1898), published in the scientific journal The American Naturalist. Using this data, regress the number of cricket chirps per minute (y) on the temperature (x).
- Create a graph showing the number of chirps per minute vs. temperature.
- Report the equation of the line.
- Report the R2 value.
- Predict the number of cricket chirps per minute at 65° F. Show your work.
- How well does your linear regression fit your data? Explain in 2–3 sentences.
- Irises are beautiful purple flowers that grow in temperate climates. Different species of irises may have different traits. Perform a t-test to determine whether the sizes of petals differ between the Virginia iris and the bristle-pointed iris. The data are attached as “04 Iris petal data”.
- Create a bar graph showing the average petal size for each species of iris with error bars for standard deviation.
- Report the p-value from the t-test.
- Which species of iris has larger petals? Interpret your p-value and explain in 1–2 sentences.
- Fertilizers provide supplemental nutrients for growing plants. Use a t-test to determine whether fertilizer A or fertilizer B results in a higher yield of corn (“yield” is the amount of corn that’s produced in an area). The data are attached as “05 Fertilizer efficacy data”.
- Create a bar graph showing the average yield for each type of fertilizer with errors bars for standard deviation.
- Report the p-value from the t-test.
- Which type of fertilizer was better (results in a higher yield)? Interpret your p-value and explain in 1–2 sentences.
Deliverables
A single document with your numbered and typed answers to the five questions above. Use 12-point Times New Roman with regular line spacing (single-spaced). Name the file “Data analysis_Lastname” and upload as a standard Word document (.docx) or PDF (.pdf).
Grades
This assignment addresses course outcome 1 and module learning objectives 1 and 2 and is worth a total of 30 points.
- Each question is worth 6 points.
- For questions with three subparts, each subpart is worth 2 points.
- For questions with five subparts, the first four subparts are each worth one point and the last is worth two.
