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Integration and Reflection For MAT201 Basic Statistics (Essay Sample)


Discuss how this course improved your quantitative reasoning and problem solving. Are there any concepts that you can apply in your personal or professional life? Identify and discuss two topics that you enjoyed learning.


Module 6: Integration and Reflection for MAT201 Basic Statistics
The focus on quantitative reasoning highlights the need to recognize, understand and evaluate quantitative information to support positions. One can solve problems better, through using quantitative information, which relies on mathematical information to inform decisions. Quantitative reasoning is not only applicable in education, but professional life and everyday settings this includes the graphical representation of data, analysis and data interpretation. At other times, quantitative reasoning allows users of information to make prediction by identifying patterns. Interpretation can be made from small to large datasets based on the reliability of data, with data statistics establishing the strength of relationships between variables.
I have learned the value of making informed decisions when faced with various possibilities when comparing samples. Data collection is paramount to data analysis, and the samples need to represent the population, with a suitable sample size. Even in cases of small sample size that have all the population characteristics, the results are relied upon to infer certain aspects of the population (Healey, 2012). The concept of hypothesis testing and identifying errors is interesting since judgments to be made from samples dependent on the tests conducted and their statistical significance.
The measures of central tendency and dispersion are widely used since they condense data and allow comparisons. Many of the statistical analyses are also based on the measures of central tendencies, which also describe data distributions (Lee et al., 2000). Most of the data values cluster around the mean, and as the sample size increases the sample mean approaches the population means (Vercruyssen & Hendrick, 2011). This highlights the relationship between the measures of central tendency and data distributions. Overall, statistical analysis provides information necessary to make informed decisions, and the assumption that data sets are normally distributed facilitates hypothesis testing. ...
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