Exercices Introduction to Statistics course (original) (raw)

statistical method and data analysis

Statistical methods shows entire procedure by which entire behavior of a population are observed in a representing sample from particular population. In wide and singular sense statistics refer to statistical methods. Generally scientists are not following Abstract censuses of populations, they preferred it as sampling. Increased demand in statistics and decreasing cost of statistics are main responsible factors for development of statistics .statistical methods are grouped under two heads statistics as a data, statistics as a Methods. Main originating source of statistics are Government records and Mathematic Therefore sampling and statistical inference are considered essential for required achievement. Making mistake in analytical works used in statistical methods is unavoidable. a important aspect of quality control is detection of random and systematic error . Care should be taken for ERROR, ACCURACY, PRECISION and BIAS in statistical results General principles for the planning of experiments and data visualization. Choice of standard statistical models and methods of statistical inference. (Binomial, Poisson, normal).Application of these models to confidence interval, estimation and parametric hypothesis testing including two-sample situations, the purpose is to compare two (or more) populations with methods using many randomly computer-generated samples are finally introduced for estimating characteristics of a distribution and for statistical respect to their means or variances. (2) Non-parametric inference tests are also described in cases where the data sample distribution is not compatible with standard parametric distributions. (3) Re sampling inference. The following section deals with methods for processing multivariate data. Methods for Dealing with clinical trials are also briefly reviewed.

Variables and their measurement

This book aims to help people analyze quantitative information. Before detailing the 'hands-on' analysis we will explore in later chapters, this introductory chapter will discuss some of the background conceptual issues that are precursors to statistical analysis. The chapter begins where most research in fact begins; with research questions. A research question states the aim of a research project in terms of cases of interest and the variables upon which these cases are thought to differ. A few examples of research questions are: 'What is the age distribution of the students in my statistics class?' 'Is there a relationship between the health status of my statistics students and their sex?' 'Is any relationship between the health status and the sex of students in my statistics class affected by the age of the students?' We begin with very clear, precisely stated research questions such as these that will guide the way we conduct research and ensure that we do not end up with a jumble of information that does not create any real knowledge. We need a clear research question (or questions) in mind before undertaking statistical analysis to avoid the situation where huge amounts of data are gathered unnecessarily, and which do not lead to any meaningful results. I suspect that a great deal of the confusion associated with statistical analysis actually arises from imprecision in the research questions that are meant to guide it. It is very difficult to select the relevant type of analysis to undertake, given the many possible analyses we could employ on a given set of data, if we are uncertain of our objectives. If we don't know why we are undertaking research in the first place, then it follows we will not know what to do with research data once we have gathered them. Conversely, if we are clear about the research question(s) we are addressing the statistical techniques to apply follow almost as a matter of course. We can see that each of the research questions above identifies the entities that I wish to investigate. In each question these entities are students in my statistics class, who are thus the units of analysis – the cases of interest – to my study.