How to Design a Data Analysis Plan for Biotech Experiments Assignment

Assignment Task

Purpose

1. Use analytical and data management skill you have developed so far to analyse a set of experimental data.

2. Use classical statistics to test various aspects of typical research data set.

3. Produce outputs for Linear and Multiple Linear Regressions models.

4. Transfer your analysis tables, and figures to a Word document and prepare a scientific report based on the data, information provided and analytical results.

5. Produce maximum a 3-page report (excluding the front page) so total 4 pages.

6. Submit a PDF version of your report to Turnitin by a deadline which will be published on Moodle and during lecture.

Data Overview and Background

You have performed Biotechnological experiments at two locations in the same planting season on a farm. New and Old fertilizer formulation were tested at the two locations at Greenwich and Medway greenhouses. A total of 25 samples were analysed at the time of harvest by extracting essential oil from the plants. The average weight (pound (lb)) and height (inches (in)) of each plant were measured and the amount of expensive essential oil (BioOil) yield were extracted in the laboratory by a Soxhlet apparatus in the setup below in Figure 1. A screen shot of the data to be analysed is shown in Table 1.

Activity 1

1. Download the uncompleted excel data Plant Growth Index (PGI) PGIData.xlsx from Moodle and save it into a Research folder on your computer.

2. Perform the necessary calculations to complete the table. 

3. You have to convert the height of the plant from inches(in) to meters (m) and also convert the weight in pounds (lb) to kilograms (kg) using the appropriate conversion factors (Do a search on the internet to see if you can get some information about how to convert).

Activity 2

1. Make a copy of the sheet and name it appropriately e.g. PGIData2. It will be a good idea to create other sheet to help manage your data and your analysis.

2. In this sheet you will carefully SORT the data by Location and perform a t-test at p=0.05 between locations for the significance of PGI (kg/m2 ) and also BioOil (mg/g) content. Be careful not to mix up your data.

3. In this sheet you will carefully SORT the data by Fertilizer type and perform a t-test at p=0.05 between locations. Be careful not to mix up your data.

4. You will also calculate the mean Oil content by Location and Fertilizer type and plot a bar graph with error bars by Location and type of fertilizer.

Activity 3

1. Generate regression output/graph between Height (m) [x1] and BioOil (mg/g) [Y] and use the equation to estimate Y and find the R2 value. Estimate the oil content of a plant 58 inches and weight 147pound? (remember to convert the units)

2. Generate a regression output/graph between Weight (Kg) [x2] and BioOil (mg/g) [Y] and use the equation to estimate Y and find the R2 value. Estimate the oil content of a plant 58 inches and weight 147pound?

3. Generate a regression output between PGI (kg/m2 )[x] and BioOil (mg/g) [Y] and use the equation to estimate Y and find the R2 value. Estimate the oil content of a plant 58 inches and weight 147pound?

4. Generate a regression output Height (m) [x1], Weight (Kg) [x2], PGI (kg/m2 )[x3] and BioOil (mg/g) [Y] and use the equation to estimate Y and find the R2 value. Estimate the oil content of a plant 58 inches and weight 147pound?

5. Compare the relationship between the Y value and the estimated Y values for each regression model and determine which of the relationships have the worse and best correlations.

Activity 4

1. Copy and paste tables and graphs of your choice after the analysis into a Word document report file and label tables and figures appropriately.

2. Format the report to include Introduction, Analytical Methods, Table of Results, Figures, Discussions, Conclusions and Recommendations.

This Data Science has been solved by our PhD Experts at My Uni Paper.