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Inferential statistics is a branch of applied statistics used to derive estimates in a population and draw conclusions based on different hypotheses testing methods. Inferential statistics gives students a hard time. If you have homework in inferential statistics that is giving you a hard time, hire an expert here for help. We have highly qualified applied statistics online tutors who work day and night to ensure that you get your dream grades. By asking for help on applied statistics here, you enjoy timely, high quality and affordable solutions. Our service is global, and we have maintained low prices because most of our clients are students without a regular means of income. Note that our experts are available 24/7, and therefore you can reach out to us at any time of the day. Therefore, if you are looking for an applied statistics homework help team that can guarantee you top grades, hire an expert here. You will enjoy effectiveness, efficiency and flexibility.
Applied statistics refers to the application of statistical methods of data analysis in coming up with a problem-solving conclusion and to aid decision-making. Any industry that deals with delivering goods and services to large markets require applied statistics to make strategic business decisions that will yield profitability. This is mainly due to the dynamic nature of markets and the factors influencing the business. It encompasses the processes of data collection, analysis, interpretation and presentation. Data collection involves methods of random sampling, experiments and observational study. Analysis requires the use of statistical algorithms and in some instances software and machine learning techniques. Finally, the presentation is where the data has to be presented in a visual way that is easy to understand. This mainly makes use of statistical plots and graphs.
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Inferential statistics is all about using data analysis techniques to find out the underlying characteristics of the population. Unlike descriptive statistics, which is focused on the observable characteristics, inferential statistics are more of estimates.
Types of inferential statistics
- Confidence Intervals
- T-test or ANOVA
- Bi-variate regression
- Pearson Colleration
- Multi-variate Regression
- Chi-square statistics
- Contingency tables
- Hypothesis test
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Stochastic processes are mathematical objects defined as a family of random variables. They are mainly used as mathematical models of system that appear to vary randomly. Do not get stressed over your stochastic processes homework because we are here to help you. Our applied statistics homework solvers are always available to give you a helping hand. We cover all topics in stochastic processes, and therefore, whichever topic is giving you a hard time, we are here to ensure that you get the right applied statistics tutor to help. To ensure that the right quality is achieved, we do all homework from scratch. This means that by hiring us, you will never have plagiarism issues. What is more, we ensure that all homework is delivered before the deadline. Therefore, instead of struggling with your complex homework, reach out to us for the best applied statistics homework help.
Stochastic processes are grouped into:
|Random walks||Markov processes|
|Gaussian processes||Random fields|
|Branching processes||Renewal Processes|
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Non-parametric tests are statistical analysis methods that do not need distribution to achieve the required assumptions to be analyzed. Non-parametric tests are an alternative to parametric tests like ANOVA or T-tests. You should use non-parametric tests if:
- The population sample is too small
- The data being analyzed does not meet the assumptions about the population sample
- The analyzed data is normal
Types of non-parametric tests
- Mann-Whitney U test
- The Kruskal Wallis test
- Wilcoxon signed tank test
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This mainly focuses on the quantitative description or statistical data. The major significance of descriptive statistics is that it largely summarizes massive data and easily visualizes the data. This makes it very easy to understand and come up with quick decisions.
In descriptive statistics, data can be summarized in two ways. One way is the use of summary graphs and tables. These give a quantitative overview of the data and make it simple to draw quick conclusions by just taking a glance. The other way is to use univariate analysis techniques. These include measures of central tendency and measures of dispersion.
Types of Descriptive Statistics
|Frequency Distribution||Frequency distribution is a presentation of grouped data categorized based on mutually exclusive classes and the number of occurrences. The main charts used in frequency distribution include bar charts, pie charts, histograms and line charts|
|Central tendency||Central tendency can be described as a descriptive dataset summary using one value that reflects the data distribution center. Measures of central tendency include mean, mode and median.|
|Variability||Variability determines how far data points appear to fall from the center. In variability variance, range and standard variation are used to depict different components of the spread.|