Next Page content If an organization is considering whether to collect data on its own or get help from an external consultant, it will need to have enough information to make an informed decision about how to proceed. This section outlines some of the key considerations that may arise during various steps in the data collection process. There is no requirement that these steps be followed or pursued in the order that they are written. The model presented is offered as a reference tool.
Overview[ edit ] In applying statistics to a problem, it is common practice to start with a population or process to be studied. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal". Ideally, statisticians compile data about the entire population an operation called census.
This may be organized by governmental statistical institutes. Descriptive statistics can be used to summarize the population data. Numerical descriptors include mean and standard deviation for continuous data types like incomewhile frequency and percentage are more useful in terms of describing categorical data like race.
When a census is not feasible, a chosen subset of the population called a sample is studied. Once a sample that is representative of the population is determined, data is collected for the sample members in an observational or experimental setting.
Again, descriptive statistics can be used to summarize the sample data. However, the drawing of the sample has been subject to an element of randomness, hence the established numerical descriptors from the sample are also due to uncertainty.
To still draw meaningful conclusions about the entire population, inferential statistics is needed. It uses patterns in the sample data to draw inferences about the population represented, accounting for randomness.
These inferences may take the form of: Inference can extend to forecastingprediction and estimation of unobserved values either in or associated with the population being studied; it can include extrapolation and interpolation of time series or spatial dataand can also include data mining.
Sampling[ edit ] When full census data cannot be collected, statisticians collect sample data by developing specific experiment designs and survey samples.
Statistics itself also provides tools for prediction and forecasting through statistical models.
The idea of making inferences based on sampled data began around the mids in connection with estimating populations and developing precursors of life insurance. Representative sampling assures that inferences and conclusions can safely extend from the sample to the population as a whole.
A major problem lies in determining the extent that the sample chosen is actually representative. Statistics offers methods to estimate and correct for any bias within the sample and data collection procedures.
There are also methods of experimental design for experiments that can lessen these issues at the outset of a study, strengthening its capability to discern truths about the population. Sampling theory is part of the mathematical discipline of probability theory.
Probability is used in mathematical statistics to study the sampling distributions of sample statistics and, more generally, the properties of statistical procedures. The use of any statistical method is valid when the system or population under consideration satisfies the assumptions of the method.Hardware Services.
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Print Reference this. Research methods involved collection of data (Bryman & Bell ) and number of methods are highlighted to collect data such as questionnaire, interview (structured or semi-structured interview) or observation method.
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Data Collection Data Collection is an important aspect of any type of research study. Inaccurate data collection can impact the results of a study and ultimately lead to invalid results. Data collection methods for impact evaluation vary along a continuum.
3 APPLYING TECHNIQUES FOR COLLECTING DATA: Collection of data procedure obeys a certain method in order to sustain consistency in your dissertation.
Studies in anthropology, geography, or sociology often require fieldwork, that is to say, using techniques such as observation and questionnaires.