Statistics Is The Study Of The Collection, Analysis, And Organization Of Data

We conduct an independent sample t-test using Excel, and obtain the following output (see t-test-height)

 Inferential statistics helps us to analyze predictions, inferences, or samples about a specific population from the observations that they make. “With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone” (Trochim, 2006). The goal for this type of data is to review the sample data to be able to infer what the test group may think. It does this by making judgment of the chance that a difference that is observed between the groups is indeed one that can be counted on that could have otherwise happened by coincidence. In order to help solve the issue of generalization, tests of significance are used. For example, a chi-square test or T-test provides a person with the probability that the analysis’ sample results may or may not represent the respective population. In other words, the tests of significance provides us the likelihood of how the analysis results might have happened by chance in a scenario that a relationship may not exist between the variables in regards to the population that is being studied.

• Provide at least two examples or problem situations in which statistics was used or could be used.

To view the research on a nominal scale, the research data can be drawn from the type of class. The word nominal is derived from the root word in Latin for name (Usable Stats, 2013). The name of the class, Psychological Statistics, is the nominal measurement for this research. When conducting this study, the study will only be measured during the course of this specific class. The results could drastically change when considering another type of class such as Quantitative Literacy as the cognitive understanding of such a collegic math class may be more optimal through a different course-delivery format.

A statistic is a numerical summary of a sample and a parameter is a numerical summary of a population.

Assuming unequal variances, the two sampled t-Test was applied on the data sets of female and male shoe sizes with the alpha value of 0.05. The null hypothesis was that the female and male shoe sizes have an equal mean while the alternative hypothesis was that female and male shoe sizes do not have an equal mean. With the degrees of freedom being 27, the t-statistic is -8.16. The probability that -8.16 is ≤ -1.70 is 4.5×10-9 for the one-tailed test. Also, the probability that -8.16 is ≤ ±2.05. is 9.1×10-9 for the two-tailed test. Given that both probabilities are under the alpha value of 0.05, the null hypothesis is therefore rejected, and the alternative hypothesis is accepted at the 95% confidence level.

Statistics uses math to determine whether or not an experiment happened by chance. In other words, it determines the probability of your results being by chance or if it is factual data. The mathematical ways of determining probably include looking at mean, standard deviation, mode, and median. This experiment will use statistics to test the probability.

The mean (x) is a measure of _central__________ __tendency___________ of a distribution while the SD is a measure of __dispersion___________ of its scores. Both x and SD are _descriptive___________ statistics.

Statistics involves framing questions in a context, then collecting and analyzing data for interpretation. Probability is about chance and fairness with assigned values. Many mathematics instructors teach this discipline in a procedural manner, causing students to miss its essence.

This report implements material covered from Chapters 4 – 6: Measures of Central Tendency; Measures of Dispersion; and Probability Distribution. The format in the report uses a question and answer narrative to clarify presentation. The report aims to answer the instructor’s questions for “Assignment 2” and information was extracted from two assigned research studies.

Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire population or a sample of it. Descriptive statistics are broken down into measures of central tendency and

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Use the given degree of confidence and sample data to construct a confidence interval for the population proportion. 1) Of 346 items tested, 12 are found to be defective. Construct a 98% confidence interval for the percentage of all such items that are defective. A) (3.34%, 3.59%) B) (1.18%, 5.76%) C) (1.85%, 5.09%) D) (0.93%, 6.00%) E) (0.13%, 6.80%) 2) Of 81 adults selected randomly from one town, 64 have health insurance. Construct a 90% confidence interval for the percentage of all adults in the town who have health insurance. A) (71.6%, 86.5%) B) (67.4%, 90.7%) C) (70.1%, 87.9%) D)

Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities. Statistics are also used for making informed decisions – and misused for other reasons – in all areas of business and government. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both

This video introduces new vocabulary terms. First of all, statistics is the study of variability. Secondly, statistics is broken down into two parts descriptive and inferential. Descriptive is when you collect data and talk about it. Inferential is when you take a sample and use it to make an inference about the population. Thirdly, the video talks about the difference between population and sample. Sample is a smaller part of the population. When you take a sample and come up with an average, that average is called a statistic. When you find the average of population, that average is called a parameter. Lastly, gathering information about the whole population is called a census. In conclusion, a statistic based on a sample helps make an inference about the parameter of the whole population.

So while I never want to take a statistics course, and while statistics scientifically involves so many numbers and mathematical principles, I am now interested in seeing how statistics is different from what everyone has said. It is wonderful to think that everyone can be connected through these