KIN 4310 1st Edition Lecture 2Outline of Last Lecture I. Section 1 TopicsII. The Scientific MethodIII. Scientific KnowledgeIV. Examples of HypothesisV. Examples of Hypothesis 2VI. Examples of Hypothesis 3VII. Examples of Hypothesis 4VIII. DefinitionsIX. Types of DataX. DefinitionsXI. DefinitionsXII. DefinitionXIII. Types of StatisticsXIV. Chapter 2XV. DefinitionXVI. Mean (Arithmetic Mean)XVII. NotationXVIII. NotationXIX. DefinitionsXX. Finding the MedianXXI. DefinitionsXXII. Which Measure of Central Tendency to UseXXIII. When to Use Mode?XXIV. When to Use Median?XXV. When to Use Mean?Outline of Current Lecture I. Excel FunctionsII. VariabilityIII. Why Variability is Important?IV. Measures of VariabilityV. DefinitionVI. DefinitionVII. Sample Standard Deviation FormulaThese notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.VIII. Why n-1?IX. Standard Deviation – Important PropertiesX. Things to RememberXI. Computing VarianceXII. Standard Deviation or Variance?XIII. Excel FunctionsXIV. Methodological ApproachesXV. Descriptive StudiesXVI. Correlation StudiesXVII. Experimental StudiesCurrent LectureI. Excel Functionsa. Meani. =AVERAGE(selection)b. Mediani. =MEDIAN(selection)c. Modei. =MODE(selection)ii. This mode function only shows the smallest mode, so don’t really rely on thisd. Ni. =COUNT(selection)ii. Use the SORT tool in the DATA menu to organize your dataII. Variabilitya. How spread out is the data?b. In the chart about the presidents:i. There is variability between presidentsii. There is variability within presidentiii. There is variability between democrats and republicansIII. Why Variability is Important?a. Variability: how different scores are from the meani. Spreadii. Dispersionb. So… variability is really a measure of how each score in a group of scores differs from the mean of that set of scoresc. Can be considered the average distance from the centerIV. Measures of Variabilitya. Three types of variability that examine the amount of spread or dispersion in a group of scoresi. Rangeii. Standard deviationiii. Variance b. Typically report the mean and the variability together to describe a distributionV. Definitiona. The range of a set of data is the difference between the maximum value and the minimum valueb. Range = (maximum value) – (minimum value)VI. Definitiona. The standard deviation of a set of sample values is a measure of variation of values about the meanb. The most common known measure of variabilityVII. Sample Standard Deviation Formulaa. s is always positiveb. x is the number in the samplec. x bar is the sample meand. the numerator is also called the sum of squaresVIII. Why n – 1a. The standard deviation is intended to be an estimate of the POPULATION standard deviationi. We want it to be an unbiased estimateii. Subtracting 1 from n artificially inflates the SD, making it larger1. This makes it hard to prove things – be conservative b. In other words, we want to be conservative in our estimate of the populationIX. Standard Deviation – Important Propertiesa. The standard deviation is a measure of variation of all values from the meanb. The value of the standard deviation s can increase dramatically with the inclusionof one or more outliers (data values far away from all others)i. Outliers have a big effect on standard deviationii. Ex. a 7 ft. person in our studyc. The units of the standard deviation s are the same as the units of the original data valuesX. Things to Remembera. Standard deviation is computed as the average distance from the meanb. The larger the standard deviation, the greater the variabilityc. Like the mean, standard deviation is sensitive to extreme scoresd. If s = 0, then there is no variability among scores; they must all be the same valuei. s = 0 is possibleii. it is impossible to have a (-) SD numberXI. Computing Variancea. Variance = standard deviation squaredb. So… what do these symbols represent? XII. Standard Deviance or Variance?a. Although the formulas are quite similar, the two are also quite differenti. Standard deviation is stated in original unitsii. Variance is stated in units that are squared iii. Which is easier to interpret?1. Standard deviation isXIII. Excel Functionsa. Range i. =MAX(selection) – MIN(selection)b. Standard deviationi. STDEV(selection)c. Variancei. =VAR(selection)XIV. Methodological Approachesa. Descriptive “X is Y”i. How things areii. One third of US citizens are obeseiii. This is observationalb. Correlational “X is related to Y”i. How things are in relation to other thingsii. Most people who are obese also have comorbid health compromising conditionsiii. This is also observationalc. Experimental “X causes Y”i. How things are and how they got that wayii. People with an energy imbalance will gain weight and may become overweight or obeseiii. Not observationalXV. Descriptive Studiesa. Most common type of study (he’s not sure about this)b. Describes how it isc. Observe and measure specific characteristics without attempting to modify the subjects that are being studiedd. Examples:i. Our stature studyii. Life expectancy in different countriesiii. Prevalence of Spinal Cord Injury in males and femalese. What are the facts?XVI. Correlation Studiesa. Used commonly in health science studiesb. Describes something in relation to something elsec. Observations are not manipulated, merely related to each other**d. Examples:i. Correlation between body fat percentage and aerobic fitnessii. Correlation between commuting distance and body-mass-indexXVII. Experimental Studiesa. Hard to do wellb. Apply some treatment and then observe its effects on the subjectsc. Even with a strong experimental design, you still may not get your answerd. Used sometimes in evaluation, but typically to explain descriptive evaluationse. Example:i. The Antihypertensive Effects of Fish Oilii. 14 people with high blood pressureiii. Randomized into 2 groups1. Group A: Ate fish oil diet for 4 weeks2. Group B: Ate a standard oil diet for 4 weeksiv. Measurement: Blood Pressure before and after the