Statistics Essay
Missing Works Cited
Length: 1090 words (3.1 doublespaced pages)
Rating: Orange
Open Document
Length: 1090 words (3.1 doublespaced pages)
Rating: Orange
Open Document
                                 
Statistics are necessary for scientific research because they allow the researchers to analyze empirical data needed to interpret the findings and draw conclusions based on the results of the research. According to Portney and Watkins (2009), all studies require a description of subjects and responses that are obtained through measuring central tendency, so all studies use descriptive statistics to present an appropriate use of statistical tests and the validity of data interpretation. Although descriptive statistics do not allow general conclusions and allow only limited interpretations, they are useful for understanding the study sample and establishing an appropriate framework for the further analysis in the study. Further analysis using appropriate statistical methods allows the researchers to establish correlations between independent and dependent variables, define possible outcomes, and identify areas of potential study in the future accurately. Statistics is important for researchers because it allows them to investigate and interpret the data more accurately, and researchers will notice patterns in the data that would be overlooked otherwise and result in inaccurate and possibly subjective conclusions (Portney & Watkins, 2009).
Frequency distribution is a method used in descriptive statistics to arrange the values of one or multiple variables in a sample, so it will summarize the distribution of values in a sample. Frequency distribution is the most basic and frequently used method in statistics because it creates organized tables of data which can be used later to calculate averages or measure variability. The organized data frequency distribution provides continuous data that is easier to work with than raw data obtai...
... middle of paper ...
...loser to the population mean and the plot would display a normal curve because a sampling distribution always forms a normal curve (Portney & Watkins, 2009). When the frequency distribution graph shows a normal curve, it is possible to determine its variability and estimate the standard error of the mean in compliance with the sample data. Unlike probability, an estimate of the population distribution allows researchers to establish the probability of selecting a sample with a predictable mean. Although the sampling distribution for predicting single outcomes is not applicable in reality, sample data can be used to draw inferences about the entire population from one sample, but it is never used to measure variance directly.
However, sample data finds applications in several researches that require estimating unknown population parameters (Portney & Watkins, 2009)
Frequency distribution is a method used in descriptive statistics to arrange the values of one or multiple variables in a sample, so it will summarize the distribution of values in a sample. Frequency distribution is the most basic and frequently used method in statistics because it creates organized tables of data which can be used later to calculate averages or measure variability. The organized data frequency distribution provides continuous data that is easier to work with than raw data obtai...
... middle of paper ...
...loser to the population mean and the plot would display a normal curve because a sampling distribution always forms a normal curve (Portney & Watkins, 2009). When the frequency distribution graph shows a normal curve, it is possible to determine its variability and estimate the standard error of the mean in compliance with the sample data. Unlike probability, an estimate of the population distribution allows researchers to establish the probability of selecting a sample with a predictable mean. Although the sampling distribution for predicting single outcomes is not applicable in reality, sample data can be used to draw inferences about the entire population from one sample, but it is never used to measure variance directly.
However, sample data finds applications in several researches that require estimating unknown population parameters (Portney & Watkins, 2009)
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