MATH1324: Introduction to Statistics Assignment Help

Statistics can be defined as that branch of mathematics which is related to the collection and interpretation of large amount of data. The process is applied in different fields for analysing different problems. The course – introduction to statistics is taught to students pursuing degree in mathematics. The course covers concepts related to probability, random variables and probability distributions, point estimation, linear regression and correlation. The aim of the discipline is to teach how to apply statistical techniques to real world problems. The course is quite important for science and business related subject. It is quite easy if studied under proper guidance. It involves implication of different mathematical formulae. No doubt the chances of mistakes are high as it involves lengthy calculations. If your academic grades are low in stats then you can hire Myassignmenthelp tutors to help you in statistics problem. We provide proficient services in statistics assignments, thesis, projects and homework.

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Topic we would cover in MATH1324:

1. Descriptive Statistics
2. Descriptive vs. Inferential
3. Means, Medians, and Modes
4. Variability
5. Linear Transformations
6. Position
7. Dispersion Percentages
8. Graphs and Displays
9. Histograms
10. Medians, Modes and Means Revisited
11. z-Scores and Percentile Ranks Revisited
12. Stem and Leaf Displays
13. Five Number Summaries and Box and Whisker Displays
14. Probability
15. Introduction
16. Random Variables
17. Expected Value
18. Variance and Standard Deviation
19. “Shortcuts” for Binomial Random Variables
20. Probability Distributions
21. Binomial Distributions
22. Poisson Distributions
23. Normal Distributions
24. Definition and Properties
25. Table of Normal Curve Areas
26. Working Backwards
27. As an Approximation to the Binomial
28. The Population Mean
29. The Distribution of Sample Means
30. Confidence Interval Estimates
31. Choosing a Sample Size
32. The Hypothesis Test
33. More on Errors
34. Type I Errors and Alpha-Risks
35. Type II Errors and Beta-Risks
36. Comparing Two Means
37. Confidence Interval Estimates
    
    

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