Aperçu des sections
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Institute : Science and Technology
Department: Process Engineering (PE)
Target public: Second-year Process Engineering
Fields of Specialization: Mathematics
Course title: Probabilities and Statistics
Credit: 2
Coefficient: 2
Duration: 15 weeks
Weekly timetable: 1h 30 min of course and 1h 30 min hours for tutorial group
Place of teaching: Lecture hall 3 classroom 10
Teacher: Farouk KECITA
Contact: kecita.f@centre-univ-mila.dz
Evaluation methods: A final exam, short test.
Recommended Prerequisite Knowledge:
Math1 and Math2 -
1_ Summarizing Data: Descriptive statistics help in providing clear quantitative summaries of data through measures such as mean, median, and mode, making it easier to understand the characteristics of the data.
2_ Describing and Interpreting Data (Pattern Analysis): Descriptive statistics allow for the analysis of patterns and trends in the data, aiding in the discovery of important relationships and characteristics.
3_Data Visualization: Descriptive statistics use graphs and tables to represent data visually, making it easier to interpret the results.
4_ Understanding Data Characteristics (Evaluating Dispersion): Through measures such as standard deviation and variance, the extent of data dispersion around the mean can be assessed.
5_ dentifying Outliers: Helps in identifying values that differ significantly from the rest of the data.
6_ Comparing Data (Analyzing Differences): Descriptive statistics can be used to compare different data sets and identify differences and similarities between them.
7_ Providing the Basis for Inferential Analysis (Preparing Data): Descriptive statistics help in preparing data for inferential analysis, such as hypothesis testing and regression analysis.
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Studying descriptive statistics requires some prerequisite acquisitions to ensure a better understanding and effective application of statistical concepts and skills. Here are some essential prerequisite acquisitions needed by students before starting the study of descriptive statistics:
1. Understanding Basic Mathematics: Basic algebra, roots, and fundamentals.
2. Knowledge of Arithmetic Operations: Familiarity with averages and basic statistical calculations and dealing with data sets.
3. Basic Knowledge of Graphs: Reading graphs and tables and creating simple graphs.
4. Ability to Think Critically: Analyzing data and asking questions.
5. Basic Principles of Statistics.
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جلطو جيللي، الحصاء مع تمارين ومسائل محلولة، ديوان المطبوعات الجامعية، الطبعة الثامنة، الجزئر، .2313
_ حليمي عبد القادر، مدخل إلى الحصاء، ديوان المطبوعات الجامعية، الطبعة الخامسة، الجزائر، .2332
_ حيدوشي عاشور، محاضرات في الحصاء الوصفي، مطبوعة موجهة لطلبة السنة الولى جذع مشترك، جامعة أكلي محند أولحاج
البويرة، الجزائر.
_ "The Basic Practice of Statistics" by David S. Moore, William I. Notz, and Michael A.
Fligner.
_ "Introduction to the Practice of Statistics" by David S. Moore, George P. McCabe, and
Bruce A. Craig.
