Confidence Intervals Summary

When conducting research data is gathered from a sample. The data can prove or disprove the hypothesis. When reviewing the data, a person can become bias and only use the data that they feel is beneficial to their study. Rubin and Babbie (2014) write about the two types of sampling bias: Conscious and Unconscious. The authors state “When we speak of bias in connection with sampling, this simply means those selected are not typical or representative of the larger populations from which they have been chosen” (Rubin & Babbie, 2014).

In the science of Psychology, observations and inferences are equally important. Observation is the act of perceiving, of noticing, of watching something closely. On the other hand, inference is looking at the evidence in front of you and making a deduction of your own based on what you see. When somebody observes something or someone they just state the facts as they appear before their eyes, whereas in inference they reach a conclusion by assuming or deducting things as well. For example, an observation would be “

 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.

According to Schutt (2008), sampling is defined as a subset of population used in a study to be a representation of the population as a whole. My final project is a pre-hire assessment which analyzes potential risky pattern behaviors and emotions in the work place. One of the most important considerations related to sampling that will need to be addressed in my final project is defining the population that will be taking the assessment.

Explain each sampling technique discussed in the “Visual Learner: Statistics” in your own words, and give examples of when each technique would be appropriate.

Identity not only mean your name and sex but it also means what and who you are as a person and how you act as a person. In “The Myth of the Latin Woman: I Just Met a Girl Named Maria” – Judith Ortiz Cofer, “Gendered Interaction: Masculine and Feminine Styles...” – J.T. Wood, and “The Confidence Gap” – Katty Kay and Claire Shipman identity is a major theme that is talked about. In “The Myth of the Latin Woman: I Just Met a Girl Named Maria” the main argument is that Hispanic women often struggle being identified. In “Gendered Interaction: Masculine and Feminine Styles...” J.T. the main argument being made is that women and men have different ways of communicating. In “The Confidence Gap” the main argument being made is that women’s lack of confidence affects their work life in a negative way. Identity is related to the three reading passages because it states how women and men are identified in certain aspects of their life.

The confidence interval is used as a type of interval estimate of a sample population to indicate the reliability of the

Media and technology is shaping our society today. Women are being viewed as just objects instead of human beings. The ideal image of beauty has changed due to the media and technology. Considering this, woman's value depends on how they look.

You take a random sample of 51 reduced-fat cookies and test them in a lab, finding a mean fat content of 4.2 grams. You calculate a 95% confidence interval and find that the margin of error is ±0.8 grams. A) You are 95% confident that the mean fat in reduced fat cookies is between 3.4 and 5 grams of fat. B) We are 95% confident that the mean fat in all cookies is between 3.4 and 5 grams. C) We are 95% sure that the average amount of fat in the cookies in this study was between 3.4 and 5 grams. D) 95% of reduced fat cookies have between 3.4 and 5 grams of fat. E) 95% of the cookies in the sample had between 3.4 and 5 grams of fat. Determine the margin of error in estimating the population parameter. 12) How tall is your average statistics classmate? To determine this, you measure the height of a random sample of 15 of your 100 fellow students, finding a 95% confidence interval for the mean height of 67.25 to 69.75 inches. A) 1.5 inches B) 0.25 inches C) 1.06 inches D) 1.25 inches E) Not enough information is given. 12) 11) 10)

Statistical inference is the second part of statistics. Statistical inference uses the data that was gathered and organized by descriptive statistics in order to make a logical inference or conclusion. There are two branches of inferential statistics: Bayesian inference and frequency probability. Bayesian inference uses the scientific method to increase the probability that a hypothesis or theorem might be true by presenting factual information. By collecting evidence, the credibility of a hypothesis can change greatly. Evidence can be collected to prove, or disprove the hypothesis. A hypothesis that has been supported by enough evidence should be accepted as true, and a hypothesis that has been rejected by enough evidence

Hi, Janet another example of Confidence Interval would be when we are following a recipe when we cook. Most recipes calls for certain ingredients and measurements to achieve a specific taste. For example, one clove of garlic, two teaspoons of water, a cup of that, and etc. We cannot be certain that the original cook followed the recipe without any error. Did the cook really use one clove a garlic, or was the teaspoon measured correctly. This is the Confidence Interval. Great

Consider the following question: someone takes a sample from a population and finds both the sample mean and the sample standard deviation. What can he learn from this sample mean about the population mean?

-The sampling distribution is a distribution of the results if all possible samples are selected, where as a population distribution is the distribution of a particular variable of interest.

According to Hair et al. (2003), in the research, the sampling process enables identifying, developing and understanding an interested object that need to be determined (p.333). Hence, in order for the researcher to carry out the sampling appropriately, advantages and disadvantages of the various sampling methods should be considered along with the theoretical component of the study (Hair et al. 2003, p. 368 f). Theoretically, the sampling procedure is divided into two major types which consist of probability and nonprobability sampling. In probability sampling, individuals have a known chance of being selected. While, in non-probability sampling, individuals do not have a known possibility to be selected (Sekaran 2003, p. 269 f). Also, the different sampling methods provide different advantages and disadvantages. Hence, the researcher should consider this point before choosing the sampling method for the