It involves the statistical analysis of statistical data and the conduct of statistical analysis of statistical data. The course also includes the statistical analysis of financial statements and other statistical data. The course also includes statistical analysis of statistical data related to statistics and statistical analysis of financial data. The course also includes the statistical analysis of statistical data related to general statistics and individual statistics. The course also includes the statistical analysis of statistical data related to applied statistics. The course also includes the statistical analysis of statistical data related to statistical forecasts and applied statistics for forecasts.
Intended learning outcomes
A.1 The student should familiarize himself with the different methods of descriptive statistics of data.A.2 The student interprets the sample data and generalizes the results to the population under study.A.3 The student should familiarize himself with the different types of statistical samples.A.4 The student should recognize the difference between random and non-random samples and the properties of each.a. Mental skillsB.1 The student should distinguish between the different types of statistical data.B.2 The student should compare the results of two or more samples drawn from independent or related communitiesB.3 The student deduces the relationship between two or more variables and determines the degree and type of relationship between them.B.4 The student should distinguish between the methods of statistical statistical analysis and the non-parametricB. Practical & professional skillsC. 1 The student should use descriptive statistics to properly summarize his data.C.2 The student should distinguish between parametric and non-parametric statistical tests.C.3 The student should store his data and the results of the statistical analysis electronically.C.4 The student should use statistical inference to reach the results of the study under discussion.T. Generic ad transferable skillsD.1 The student should be able to use one of the statistical programs to save practical studies data electronically, such as Minitab, or SPSS...etc.D.2 The student should be able to perform statistical analysis using Minitab, SPSS, or other statistical programming.D.3 The student should be able to use the appropriate statistical method in analyzing data according to the nature of the study.D.4 The student should be able to comprehend the statistical terminology related to his specialization.
Evaluation number Evaluation methods Evaluation period Evaluation weight Percentage Evaluation date (week) NotesThe first assessment is a short theoretical exam of 45 minutes, 15 marks, 15%. The thirdThe second assessment is a theoretical and practical exam, two hours, 25 degrees, 25% SeventhThird Evaluation Evaluation of the worksheet 30 minutes 10 marks 10% EleventhFinal evaluation Comprehensive final exam 3 hours 50 marks 50% Sixteenth Total 100 Score 100%
Course content:
Scientific subjectSome basic concepts: data - population - sample - random variable - continuous random variable - discrete random variable - probability - statistics - descriptive statistics - inferential statistics - randomness.Sampling type: simple random sampling - stratified sampling - stratified sampling. Types of scales: nominal - ordinal - connected - discrete.Run the program SPSS or MINITABEnter - save - modify dataMeasures of central tendency: mean, median, meanMeasures of dispersion: range - variance - standard deviationrandom variables:Events: the relationship between events.Some basic concepts of probabilityDiscrete Random Variables and Probability Distributions:Binomial distribution, Poisson distribution.Continuous Random Variables and Probability Distributions:normal distribution, T-distribution, chi-squared distribution, F-distribution.Correlation and simple linear regression:Pearson correlation coefficient, Spearman correlation coefficient. Simple linear regression modelEstimation: Estimation of the population mean and variance, confidence intervals For the population mean variance and proportion. Hypothesis Test:Basic concepts (types of hypotheses - errors of the first kind - test significance - P value Parametric test conditionsTest the normal distribution of the data- homogeneity test - Hypothesis tests for the average of one population:- one-sample T-test (parametric test),- Wilcoxon Rank Test (non-parametric test) Comparison between two independent samples:- T-test (parametric test),- Mann-Whitney test (non-parametric test) Comparison of two independent samples:- Dual T test (teacher test)-, Wilcoxon test (non-parametric test) Comparison of more than two independent samples:Analysis of variance (parametric test)Kruskal-Wells test (non-parametric test) Comparison of more than two related samples: - Analysis of Variance (Parametric Test) Friedman test (non-parametric test) Independence testing and quality reconciledChi-square (ka2) test
