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please answer fast Gr.T. Popa University of Medicine and Pharmacy - Iai Medical Informatics and Biostatistics Discipline Year I - Medicine PROJECT You will randomly
please answer fast "Gr.T. Popa" University of Medicine and Pharmacy - Iai Medical Informatics and Biostatistics Discipline Year I - Medicine PROJECT You will randomly generate data in MS Excel which you will then analyse using the knowledge of biostatistics. You will have a single Excel file with six spreadsheets. Each student will name their file in the following format: MG_EN_1_"SERIES"_GR_"NO. GROUP" "FAMILY NAME" "First name"_"Name".xlsx Example: MG_EN_1_1_GR_OS_SMITH_Dan_Andrew.xlsx The student who does not follow the file name format, loses one point from the final grade. As we mentioned during the semester, if you don't have Microsoft Excel you can work in Libre Office (Libre Office Calc - Excel equivalent), or Google Sheets. Through Microsoft Teams we have defined the task you have the project, Assignment), so you have to upload the project in time to Teams. The deadline is defined by the end of the semester, that is January 15, 2022. Attention: to send the file for verification you have to click on TURN IN (obviously in time) after you have uploaded the file. Themes to achieve 1. In the first spreadsheet create a table with generic data (preferably medical) containing the following types of columns that you will then use for the statistical study. The columns whose name contains the word Variable, you will generate them randomly. using the known functions. B Category 1 1 no. 2 3 4 5 6 2 3 4 5 Variable_1 Variable_x Variable_Y 1 58 91.6 43.636 1 29 87.3 26.817 1 40 71.8 30.938 1 52 43.7 20.054 1 49 89.8 51.09 The first column (no.) is the current number - you will have at least 60 data (people involved in the study). The second column (Category) is a categorical variable, coded with O and 1. There are only two possible values defining the presence (1) and absence (C) of a condition, or in general group 1 and group 0. You will have at least 30 data per group. The third column (Variable_1) is a random variable (mandatory in the medical field). It will have integer values - at least on the order of tens. The fourth column (Variable_x) is a random variable (mandatory in the medical field). It will have values with the precision of one decimal and at least one number for the integer part. Pagina 1 din 3 The fifth column (Variable_y) is a random variable (mandatory in the medical field). It will have values with the precision of at least one decimal and at least one number for the integer part. You will copy this table to the second spreadsheet without formulas - we are only interested in numerical values. From now on, use only the data from the second spreadsheet 2 - In the third spreadsheet copy Variable_1 and calculate the statistical measures marked in red: Variable_1 Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Confidence Level(95.0%) Make a short description, next to each statistical measure (marked in red) taking into account the computed value. 3 - Copy from the second spreadsheet, the columns Category and Variable_1 to the fourth spreadsheet. Now work on the fourth spreadsheet. Separate Variable_1 according to the two groups defined by the variable Category. Compare the variances of variable 1 in the two groups created. Describe the results - write the decision briefly and motivate it by explicitly using the calculations made. 4 - We continue the analysis from the fourth spreadsheet. Copy the values of variable 1 from the fourth sheet into the spreadsheet five, grouped by category. Now work on the fifth spreadsheet Apply the appropriate test to compare the means of the two sets of variable 1. Describe the results - write the conclusions briefly and motivate them by explicitly using the calculations made 5 - Copy the columns Variable_x and Variable_y from the second spreadsheet to the sixth spreadsheet. Now work on the sixth spreadsheet. Pagina 2 din 3 Make the graph and do the regression and correlation analysis. Describe the results - write the conclusions briefly and motivate them by explicitly using the calculations made
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