# lecture vi statistics. lecture questions mathematical statistics sampling statistical population and...

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Definition of Statistics Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of experiments. Mathematical statistics is the study of statistics from a mathematical standpoint.TRANSCRIPT

Lecture VIStatistics

Lecture questionsMathematical statisticsSampling Statistical population and sampleDescriptive statistics

Definition of StatisticsStatistics is the study of the collection, organization, analysis, interpretation, and presentation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of experiments.Mathematical statistics is the study of statistics from a mathematical standpoint.

Data analysis descriptive statistics - the part of statistics that describes data, i.e. summarises the data and their typical properties.inferential statistics - the part of statistics that draws conclusions from data (using some model for the data). It uses mathematical probabilities, make generalizations about a large group based on data collected from a small sample of that group.

Sampling In statistics, sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population.The advantages of sampling are

the cost is lowerdata collection is fastersince the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data.

Statistical population and sample A statistical population is a set of entities concerning which statistical inferences are to be drawn, often based on a random sample taken from the population. (N is population size).A sample is a subset of a population. n is sample size.

Sampling process stagesDefining the population of concernSpecifying a sampling method for selecting items or events from the frameDetermining the sample sizeImplementing the sampling planSampling and data collecting

Properties of a good sampleAdequate sample size (statistical power)Random selection (representative)

Sampling methods Probability methods

random samplingsystematic samplingstratified samplingNonprobability methods

Cluster sample.Convenience sample. The advantage of probability sampling is that sampling error can be calculated.

Simple random samplesimple random sample is a subset of individuals (a sample) chosen from a larger set (a population). Each individual is chosen randomly and entirely by chance, such that each individual has the same probability of being chosen at any stage during the sampling process, and each subset of k individuals has the same probability of being chosen for the sample as any other subset of k individuals[1]. This process and technique is known as simple random sampling

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