Intro to Stats: Study Guide Exam 1
Intro to Stats: Study Guide Exam 1 ESC_PS 4170 - 06
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This 4 page Study Guide was uploaded by Amanda Furtick on Monday September 19, 2016. The Study Guide belongs to ESC_PS 4170 - 06 at University of Missouri - Columbia taught by Beiner in Fall 2016. Since its upload, it has received 33 views. For similar materials see Intro to applied statistics in Math at University of Missouri - Columbia.
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Date Created: 09/19/16
Intro to Applied Statistics: Exam 1 Study Guide This includes the main points from chapters 27. The yellow highlight is the keyword and the orange highlight is the definition or description of the key word. Chapter 2: The scientific method involves 1) defining a problem, 2) reviewing the literature, 3) dealing with the problem, 4) formulating one or more hypotheses or questions related to the problem, 5) collecting data to test each hypothesis empirically, 6) analyzing the data, 7) determining if each hypotheses is or is not supported and, 8) interpreting the results of the investigation. Qualitative research is used to answer questions verbally and show how the participants perceive and interpret aspects of the environment unstructured, words and images. Quantitative research is more standard and examines questions in numerical form data. Empirical research carryout out a firsthand investigation Basic research carried out to address one or more theoretical questions simply for purpose of addressing the questions Applied research carried out to solve reallife problems. (obtaining knowledge) Action research carried out to find what works in a particular situation with particular group of people (no generalizations) Evaluation research carried out to determine effectiveness of existing programs Chapter 3: Nondirectional hypotheses make no attempt to specify direction; indicates differences or relationships exist. Human subjects need to be protected both mentally and physically from stress. The benefits must outweigh the negatives. Validity how accurate the measure is Reliability the degree of consistency of measurement (if the test was given multiple times, the same result would always occur) Concealment occurs when the researcher tells the truth but omits information, and deception occurs when the researcher purposefully gives false information Chapter 4: A, B, X, and Y are used to represent a quantity, score, or value in a variable and N stands for “number.” An independent variable is the main variable that is used to determine if it has an effect on another variable. The dependent variable is the outcome, determined by the independent variable. Descriptive stats classify numerical data and inferential stats make a guess about the population based on a smaller sample or portion. Nominal data is categorical, simply an identification number and not a number of value. Ordinal data is the order or category of numbers, but the differences between the ranking do not need to be the same. Interval data means that the space between each number of ranking is equal but zero does not reflect the absence of something. Ratio measures the same as an interval, but zero does mean the absence of something. Parameter description of a population Sample subset of a population Chapter 5: Probability the likelihood or chance that something will or will not happen. Experiment a situation involving chance or probability that leads to results called outcomes Outcome the result of a single trial of an experiment Sample Space the set of all possible outcomes (ie: sample space of rolling a die is 1, 2, 3, 4, 5, 6) Event one or more outcomes of an experiment (ie: rolling a 3 is an event) 1 P(E) = probability of something not happening P(E) = number of outcomes corresponding to event E/total number of outcomes All probabilities between zero and 1 are inclusive. The sum of all the probabilities in the sample space is 1. The probability of an event which cannot occur is 0. The probability of an event which must occur is 1. Chapter 6: When organizing data, 1) organize data in column form from highest score to lowest score, 2) develop a frequency distribution, 3) create a grouped frequency distribution if necessary, 4) create a cumulative frequency distribution, 5) create a cumulative percentage distribution. Raw data data collected in random form Grouped data is used when there is a large number of scores and it is easier to group the intervals together. Cumulative frequency and cumulative percentage distribution are additional ways of looking at data sets. Graphs display data sets. In a bar graph and histogram, the x (horizontal) axis represents the independent variable and the y (vertical) axis represents the dependent variable. Bar graphs are good for nominal data and histograms are good for interval and ratio data. Normal bell curves are symmetrical. (leptokurtic, platykurtic, multimodal). Positively and Negatively skewed curves are not symmetrical. Chapter 7: Percentile ranks indicate the relative position of an individual in a group. Ungrouped Data: 1) create a frequency distribution, 2) create a cumulative frequency distribution. Formula for calculating percentile rank in ungrouped data: PR = cum f/n X 100 Upper limit in grouped data: add .5 to the highest value specified in the limit (ie: if the group was 100109, add .5 to 109). Lower limit in grouped data: subtract .5 from the lowest value of the limit (ie: subtract .5 from 100) Formula for calculation percentile rank in grouped data: PR = cumf n (X Xii/i)(Fi) x 100 N
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