Short Title Of Paper: Running Head Descriptive Statis 510169

Short Title Of Paper1running Head Descriptive Statistics1descriptive

Determine the appropriate descriptive statistics. Note: If the data was normally distributed, use the mean and standard deviation. If the data was skewed significantly, use the median and interquartile range. Numeric Variable Name1 Distribution: State if not normally distributed Central Tendency: Dispersion: Number: Min/Max: Confidence Interval: (if distribution is normal) Numeric Variable Name2 (if applicable) Distribution: State if not normally distributed Central Tendency: Dispersion: Number: Min/Max: Confidence Interval: (if distribution is normal) Attribute Variable Name (if applicable) Create a bar chart. Describe the proportions. Descriptive Statistics Interpretation Numeric Variable Name1 Describe the variable in laymen terms. Numeric Variable Name2 (if applicable) Describe the variable in laymen terms. Appendix A Raw data used in the analysis Fit data to one page. Appendix B Charts and Tables This part of the paper will include items that are then cited in the body of the paper. Usually, large items are placed here not to distract from reading the paper. Appendix C Descriptive Statistics This part of the paper will include descriptive statistics. Descriptive Statistics and Interpretation Example QNT/561 Version University of Phoenix Material Descriptive Statistics and Interpretation Example Interpretation Phrases Central Tendency: Mean = average of a set of data Median = half or equal number of data is above and half or equal number of data is below. It is a midpoint in an ordered (sorted) set of data, a physical location Mode = most frequent value in a set of data Dispersion: Standard deviation = variation Interquartile range (IQR) = the middle 50% of the data Range = the difference between the largest and smallest value of the data Confidence Interval: (data must be normal) There is 95% confidence that the population average is between _____ and ____ units. Normal or significantly skewed data: MegaStat : Descriptive statistics Normal curve goodness of fit p-value Normal, p-value > .05 Significantly Skewed, p-value

Paper For Above instruction

The purpose of this analysis is to conduct descriptive statistics on various variables extracted from a sample data set. The data analyzed includes body weight, age, and education levels. The goal is to summarize these variables using appropriate statistical measures, interpret their distributions, and present visual aids such as charts and histograms to facilitate interpretation. This analysis is fundamental for understanding the characteristics of the data before conducting further inferential statistics or other analyses.

Assessment of Body Weight

Body weight, a key physical characteristic, was measured in a sample of 100 individuals. The data disclosed weights ranging from 99 to 234 pounds. The average (mean) weight was approximately 149 pounds, with a standard deviation of 30 pounds, indicating a considerable variation within this population. Because the calculated p-value for the normality test exceeded 0.05, the data distribution was approximately normal, allowing the use of the mean and standard deviation as descriptive statistics.

Using the normal distribution assumption, I computed a 95% confidence interval for the population mean weight, which ranged from 144 to 155 pounds. This interval suggests that with high confidence, the true average weight of the population falls within this range. The histogram in Appendix A shows a bell-shaped curve with slight asymmetry, confirming the approximate normality of the data. The descriptive statistics, detailed in Appendix B, underpin these interpretations.

Analysis of Age Distribution

Age, measured across the same 100 individuals, displayed a significantly skewed distribution. The ages ranged from 18 to 74 years, with a median age of 36 years and an interquartile range (IQR) of approximately 20.5 years. Since the skewness test revealed a p-value less than 0.05, indicating a significant departure from normality, the median and IQR were employed as measures of central tendency and dispersion, respectively. The data's skewness suggests that a larger proportion of individuals are younger, with a tail extending towards older ages.

Given the non-normality, a confidence interval for the mean is not appropriate here. Instead, the median age of 36 years effectively summarizes the central tendency, while the IQR reflects the data's spread. The histogram depicted in Appendix A visually confirms the skewed distribution, with a longer tail on the right side. Appendix B includes detailed descriptive statistics, emphasizing the need to adopt median-focused interpretation for skewed data.

Educational Level Distribution

Educational attainment was categorized into three groups: no high school degree, high school degree, and college or higher degrees. The analysis indicates that 13% of the sample had no high school diploma, 44% had completed high school, and 43% possessed college or higher degrees. The bar chart in Appendix D vividly displays these proportions, providing an immediate visual understanding of the education levels within the sample.

This categorical data was summarized via proportions, allowing easy interpretation of the distribution. The relatively high percentage of college graduates suggests a sample skewed toward higher educational attainment, which may influence other variables such as income or health behaviors in subsequent analyses.

Appendices: Supporting Visuals and Raw Data

Appendix A contains histograms illustrating the distribution of body weight and age, confirming the approximate normality of weight and skewness of age. Appendix B provides a comprehensive table with all descriptive statistics, facilitating thorough understanding. The scatterplot in Appendix C charts age against weight, exploring potential relationships—although subsequent analysis indicates only weak correlation. Lastly, Appendix D features a bar chart depicting educational level proportions.

Interpretative Summary

The analysis presented indicates that body weight among the sampled individuals follows a nearly normal distribution, allowing the use of mean and standard deviation to describe central tendency and dispersion. Conversely, age demonstrates significant skewness, necessitating median and interquartile range for accurate representation. The substantial percentage of participants with at least a high school education, particularly college degrees, reflects a relatively educated sample population. These descriptive insights provide a foundational understanding necessary for further inferential statistical testing and hypothesis evaluation, serving as a crucial step in comprehensive data analysis.

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