Statistics - Third secondary
المستويات الدراسية:
النظام التعليمي: National English
1. Calculate and interpret correlation coefficients (Pearson and Spearman)
2. Construct and analyze regression lines using least squares method
3. Use statistical software (Excel, SPSS) for data analysis and visualization
4. Apply stem-and-leaf displays for data representation
5. Calculate quartiles and semi-interquartile ranges
6. Make predictions using regression models
7. Interpret statistical results in real-world contexts
1. Define correlation and explain its significance in data analysis.
2. Interpret and construct scatter diagrams to visualize relationships between variables.
3. Differentiate between direct (positive) and inverse (negative) correlation with examples.
4. Explain linear correlation and its characteristics.
5. Calculate and interpret Pearson’s linear correlation coefficient.
6. Calculate and interpret Spearman’s rank correlation coefficient.
7. Distinguish between types of correlation and describe their real-world applications.
8. Analyze data sets to determine the strength and direction of correlations.
1. Define regression and explain its purpose in statistical analysis.
2. Identify and describe different types of regression.
3. Explain the method of least squares for fitting a regression line.
4. Derive and interpret the regression line equation from a given data set.
5. Apply the least squares method to calculate the regression line.
6. Use the regression line equation to make predictions based on data.
1. Represent a set of data using the stem-and-leaf method.
2. Use the stem-and-leaf method to organize and display numerical data clearly.
3. Compare two or more sets of data using stem-and-leaf plots.
4. Interpret data patterns and distributions from a stem-and-leaf plot.
1. Understand quartiles and their graphical representation.
2. Find quartiles from frequency tables.
3. Find quartiles using the stem-and-leaf method.
4. Interpret and construct box plot diagrams.
1. Understand the concept of semi-interquartile range.
2. Calculate the semi-interquartile range from given data.
3. Interpret the semi-interquartile range as a measure of data spread.
1. Calculate probabilities of events and conditional probabilities
2. Distinguish between independent and dependent events
3. Analyze discrete and continuous random variables
4. Calculate and interpret probability distributions (geometric, binomial, normal)
5. Compute statistical measures (expectation, variance, standard deviation)
6. Apply normal distribution to real-world problems
7. Construct and interpret confidence intervals
1. Understand the concept of a random experiment and sample space.
2. Define different types of events: simple, sure (certain), and impossible events.
3. Perform operations on events: union, intersection, difference, and complement.
4. Explain mutually exclusive events.
5. Apply De Morgan's laws to events.
6. Understand the basic concepts of probability.
7. Calculate probabilities of events.
8. Know the probability axioms and their real-life applications.
1. Understand mutually exclusive events.
2. Understand events that are not mutually exclusive.
3. Learn about conditional probability.
1. Understand independent events.
2. Understand dependent events.
1. Understand the concept of a random variable.
2. Learn the difference between discrete and continuous random variables.
3. Understand probability distributions.
1. Understand the concept of expectation (mean) of a discrete random variable.
2. Learn about variance of a discrete random variable.
3. Understand the standard deviation and coefficient of variation.
1. Understand geometric probability experiments.
2. Learn the probability distribution of a binomial random variable.
3. Understand expectation, variance, and standard deviation of a geometric distribution.
4. Understand the binomial distribution.
1. Understand the concept of Probability Density Function (PDF).
2. Learn the key term: Probability Density.
1. Understand the concept of a normal random variable.
2. Learn some properties of the normal distribution.
3. Understand the standard normal distribution.
4. Learn properties of the density function of the standard normal distribution.
5. Calculate probabilities related to the standard normal distribution.
1. Understand practical applications of the normal distribution.
1. Estimate the mean of a population using a point estimate.
2. Estimate the mean of a population using a confidence interval.