a. In statistics, a population is a collection of individuals, things, events, etc. The population is the topic that one wants to make inferences on, whereas a sample is a subset of the population that is being collected—to be studied. After the sample is studied in statistics, one draws an inference of the population. There are four general sampling methods used in statistics: representative sample, random sample and quasi-random sample, stratified and quota sample, convenience sample, and purposive sample. A representative sample should be unbiased and thus properly indicate a characteristic of the entire population. In a random sample nothing is biased; in other words, every individual, thing or event in the population has the same chance of being selected for the sample. Therefore, because of the randomness of the sampling, the selection of one item from the population in no way effects the selection of another item. A quasi-random sample is simply a number (nth), which is …show more content…
A population is labeled finite if the measurements—individuals, events, etc.—can be counted. In contrast, an infinite population cannot be counted.
c. Descriptive statistics is a procedure of organizing sample data. This procedure allows readers to be able to understand and describe the data’s importance. Descriptive statistics allows an individual to quickly understand the data and make predict an individual score; however, descriptive statistics does not describe all data in the sample. Inferential statistics is a process that determines whether sample data accurately represented the relationship to the population. In other words, one uses inferential statistics to determine if the sample data is believable.
d. A parameter is used in inferential statistics and is used to describe the scores of a population—letters of the Greek alphabet symbolizes a parameter. An estimate in statistics is a value, which was produced by the sample, and inferred to be the value of the
Two sampling methods include mail surveys and convenience sampling, a variation of a nonprobability sample. Mail surveys, inexpensive way to contact individuals over a large geographical area, provide anonymity to the respondent, and eliminate interview bias. Convenience sampling, a nonprobability sample, the only criteria is the convenience of the unit to the researcher, fast and uncomplicated, but the sampling error not determined.
The final chapter of this book encourages people to be critical when taking in statistics. Someone taking a critical approach to statistics tries assessing statistics by asking questions and researching the origins of a statistic when that information is not provided. The book ends by encouraging readers to know the limitations of statistics and understand how statistics are
A researcher determines that 42.7% of all downtown office buildings have ventilation problems. Is this a statistic or a parameter; explain your answer.
Inferential statistics establish the methods for the analyses used for conclusions drawing conclusions beyond the immediate data alone concerning an experiment or study for a population built on general conditions or data collected from a sample (Jackson, 2012; Trochim & Donnelly, 2008). With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population might think. A requisite for developing inferential statistics supports general linear models for sampling distribution of the outcome statistic; researchers use the related inferential statistics to determine confidence (Hopkins, Marshall, Batterham, & Hanin, 2009).
First, all data have both an objective and a subjective component. Numbers can be easily assigned to all qualitative data (such as open-ended questions in surveys), and any number obtained by a quantitative study is interpreted using a subjective or qualitative judgment. Second, using differen...
The purpose is to explain, predict and or control phenomena through a focused collection of numerical data. Answers the question what, when and where. Sampling is a large population that is random. The design is structured, inflexible, specified in detail (Quantitative, Qualitative Research, 2012). Data collection focus groups and interviews. Data interruptions are conclusions and generalizations at the end of the study, never one hundred percent sure of the outcome. Used to study individual cases and find out how people think or feel (Broader, 2010). Quantitative studies provide more in-depth information that is specific to an issue can often be used for comparison. Quantitative data offer inferential statics, a collection of data about millions of people and make inferences about a target population. The data include gender, height weight, cholesterol level, waist circumference and temperature, ages, geographical region or population and can be anonymous. It helps to measure trends over time such as frequency of outbreaks of communicable diseases in a community. Quantitative enables the ability to summarize allows for comparisons over time and across categories information sources. Quantitative has higher accuracy, eliminates bias, proves or disproves a hypothesis and narrows directions if further research is needed. Quantitative can assist nurses in determine which scientific method to determine which
As a population, we are bombarded with percentages and statistics, but how does one know if what we are being told is correct? The book How to Lie With Statistics by Darrel Huff was written to help readers better understand statistics especially when they are presented to us in ways that can be misleading or misunderstood. The book is not meant as a guide on how to change or manipulate statistical numbers. However, if statistics are not presented properly or perhaps purposely misleading people, this book will help readers question or form their own opinions from data. Most people simply are not that interested when you hear the word statistics and many times people do not believe the numbers presented. This mistrust occurs most often for two reasons: the person not being able to see the raw data and where or how it was collected and the person not being able to verify the credibility of the information presented. Throughout the book, Huff discusses different statistical techniques that can be used improperly and how one can discern good statistics from those that may have been manipulated.
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
Often uses random sampling to select a large statistically representative sample from which generalizations can be drawn.
This essay is going to critically discuss the advantages and disadvantages of using surveys and questionnaires as a method of Socio-Legal research. When conducting socio-legal research, a number of methods can be used to collect useful information.
For example, in a study of criminal justice among juvenile offenders, a single child is considered a sampling unit. A sampling unit could also be a group of elements in a population that the researcher uses for choosing members of the sample population. For instance, a household of consumers could be considered as a sampling unit during marketing researchers. Sampling units usually share common characteristics thus provide the researcher with invaluable information that is useful for drawing conclusions during the research
Descriptive stats summarize data so the data can be comprehended. The researchers prepare a frequency distribution which shows the frequencies as descriptive statistics. Percentages, and averages are also descriptive statistics. Therefore, the descriptive statistics describe sets of data collected through observation. Then the statistics are organized in tables, pie charts, graphs etc. Researchers must be sure the kind of descriptive statistics matches the kind of data that has been collected.
For example, a way of combatting the non-opinions and non-attitudes that can falsify results is by giving respondents background information before they are asked the question. (Add more here?) Additionally, there are different types of sampling methods that are used to reliably draw from a random and representative portion of the population. Simple, systematic, stratified random and multistage cluster sampling are all ways of collecting data from a portion of the population to represent the opinion of the population as a whole
2. Determining the Sample Frame: A sample frame is a representation of the target population.
c. Statistical Design: It concerns with the question of how many items are to be observed and how the information and data gathered are being