This question already has collected data and is trying to find a urinary analyte that can be used as a marker of urine production rate.
should be written up as a single scientific report with introduction, aims, hypotheses, results, discussion and conclusions. The methods description only has to describe the data handling (statistical) processes that were performed.
data is attached.
Part A – Data variability
For this exercise, use the accompanying spreadsheet  to calculate the mean and standard deviation for each of the variables in this group of participants for each day that they are monitored. The male participants have 24h collections of urine for a number of days in sequence. There is missing data so ensure that you have the correct order of days and parameters.
For each excreted parameter, calculate value as an excretion rate/24h  compared to the urine volume for each day.
Plot the average data for each parameter (mean value). Use error bars to denote the SD. Put the urinary parameter on the Y axis and the urine volume for each day in sequence on the X axis.
Comment on the variability in the data for each parameter and the analytes that correlate best with urinary volume. :We use a rise in the PdG excretion rate (using timed urine samples to correct for fluctuations in urine volume to a universal threshold value of 7.0 mmol/24 h as the hormonal marker for the beginning of the Post Ovulatory Infertile Period.This activity investigates if there is a suitable urinary analyte that can be used  as an estimate of urinary volume over time (ml/min), without the need to time the collection and measure the volume.

Part B – Sample Size
For ethical and efficiency reasons, it is good practice to determine the minimum number of participants required for valid statistical analysis. This is called a Power calculation and is dependent on a  number of parameters including the variation/range in the population, normal distribution of the elected cohort, the degree of accepted confidence in the test (usually >80%) and the minimum P-value accepted as significant (usually <0.05). A company wants to test if its new formulation X is better than the current drug C. Use the following variables to calculate how many participants are required under the following circumstances:It is known from published studies that the reduction in the blood pressure of hypertensive patients can be regarded as being normally distributed during treatment with both drugs. It is also known that drug C reduces the blood pressure of hypertensive patients by a mean value of about 10 mm Hg. Previous studies indicate that formulation X is more potent than drug C and is predicted to reduce mean blood pressure by about 15 mm Hg. This is regarded as a clinically relevant improvement. Moreover, clinical knowledge suggests that the standard deviation of the reduction in blood pressure with both drugs can be taken as 5 mm Hg.The level of significance is the probability of obtaining a statistically significant test result, even when there is no real difference. This is conventionally taken as 2.5% for one-tailed tests. Nevertheless, other values would be conceivable, depending on the question to be answered. The statistical power is the probability of identifying a real difference with the statistical test and is often taken as 80%. Use the ClinCalc Sample Size Calculator to determine the number of participants required if the predicted difference in the decrease in blood pressure induced by the two drugs  is 4, 5 or 6 mmHg. Patient Mean UV mil/day SG P205 g/day Cl2 g/day nSO3 g/day 1 1532.5 1.01775 3.438333333 6.763333333 0.140166667 2 1239 1.0273 4.5 6.082 0.215 3 1812 1.0179 3.694 6.282 0.1654 4 1196 1.0259 3.822 5.91 0.1806 5 1444 1.0219 3.902 5.726 0.16 6 1242 1.0234 3.962 5.572 0.12425 7 1394 1.0196 3.76 5.488 8 1335 1.0165625 1.84625 5.1775 0.214125 9 1045 1.0164 3.73 5.796 0.197 Patient SD UV mil/day SG P205 g/day Cl2 g/day nSO3 g/day 1 437.3528324 0.001864135 0.362955461 0.426129871 0.102857993 2 111.9374826 0.001151086 0.353411941 0.72451363 0.045092498 3 117.7178831 0.001596872 0.094498677 0.657320318 0.050919544 4 335.0820795 0.005424482 0.165891531 0.73464277 0.048340459 5 87.34987121 0.001746425 0.179220535 0.404512052 0.042426407 6 324.1450293 0.004144273 0.128918579 0.817477828 0.013375973 7 205.5298032 0.004159327 0.26860752 1.077645582 0 8 828.1821746 0.004865604 0.68545996 2.188703139 0.114324647 9 173.060683 0.003577709 0.240935676 0.554869354 0.036523965 UreaN g/day UAN g/day 12.95333333 0.1525 16.208 0.146 14.332 0.111 12.768 0.6 14.152 0.1046 12.84 0.1456 13.902 0.1584 5.995 0.08875 UreaN g/day UAN g/day 1.568064625 0.020569395 1.131954063 0.011401754 0.671170619 0.008062258 0.81462875 0.288010416 0.300199933 0.016757088 0.92784697 0.036287739 0.929284671 0.071230611 1.504725889 0.032243493 0 0