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  1. 1. Welcome to Introduction to Statistics Dr. Pam Ansburg
  2. 2. What You Eat Depends On With Whom You Eat ScienceDaily (Aug. 10, 2009) — If you are a woman who dines with a man, chances are you choose food with fewer calories than if you dine with a woman. That is one of the findings in a study conducted by researchers at McMaster University. The results appear in the online version of the international journal Appetite. Meredith Young, PhD candidate in the Department of Psychology, Neuroscience & Behaviour, found that what a person chooses to eat at lunch or dinner is influenced by who they eat with and the gender make-up of the group. By observing students in naturalistic settings in three large university cafeterias with a wide choice of food options and dining companions, Young found that women who ate with a male companion chose foods of significantly lower caloric value than did women who were observed eating with another woman. What's more, when women ate in mixed-gender groups their food choices were at the lower end of the caloric scale; the more men in the group the fewer the calories. When women ate in all-female groups, their food was significantly higher in calories. "Eating is a social activity," says Young. "In university cafeterias people select their food before they are seated and perhaps before they know with whom they will eat. Given the observed differences it seems likely that social groupings were anticipated at the time of food selection." Young is not surprised by the findings. The diet industry targets female consumers and product advertisements typically depict very slim models rather than average-sized or overweight female models, she says, so food choices appear to be weighed against how other perceive them. In other words, smaller, healthier portions are seen as more feminine, and women might believe that if they eat less they will be considered more attractive to men. "It is possible that small food portions signal attractiveness, and women conform, whether consciously or unconsciously, to small meals in order to be seen as more attractive," says Young. As for men's food selections, the study showed that men were neither substantially affected by the number of nor the gender of their dining companions. From McMaster University (2009, August 10). What You Eat Depends On With Whom You Eat. ScienceDaily. Retrieved August 13, 2009, from http://www.sciencedaily.com /releases/2009/08/090805114616.htm
  3. 3. Population • The entire group of individuals is called the population. • For example, a researcher may be interested in the relation between class size (variable 1) and academic performance (variable 2) for the population of third-grade children.
  4. 4. Sample • Usually populations are so large that a researcher cannot examine the entire group. Therefore, a sample is selected to represent the population in a research study. The goal is to use the results obtained from the sample to help answer questions about the population.
  5. 5. Data • The measurements obtained in a research study are called the data. • The goal of statistics is to help researchers organize and interpret the data.
  6. 6. Descriptive Statistics • Descriptive statistics are methods for organizing and summarizing data. • For example, tables or graphs are used to organize data, and descriptive values such as the average score are used to summarize data. • A descriptive value for a population is called a parameter and a descriptive value for a sample is called a statistic.
  7. 7. Inferential Statistics • Inferential statistics are methods for using sample data to make general conclusions (inferences) about populations. • Because a sample is typically only a part of the whole population, sample data provide only limited information about the population. As a result, sample statistics are generally imperfect representatives of the corresponding population parameters.
  8. 8. What You Eat Depends On With Whom You Eat ScienceDaily (Aug. 10, 2009) — If you are a woman who dines with a man, chances are you choose food with fewer calories than if you dine with a woman. That is one of the findings in a study conducted by researchers at McMaster University. The results appear in the online version of the international journal Appetite. Meredith Young, PhD candidate in the Department of Psychology, Neuroscience & Behaviour, found that what a person chooses to eat at lunch or dinner is influenced by who they eat with and the gender make-up of the group. By observing students in naturalistic settings in three large university cafeterias with a wide choice of food options and dining companions, Young found that women who ate with a male companion chose foods of significantly lower caloric value than did women who were observed eating with another woman. What's more, when women ate in mixed-gender groups their food choices were at the lower end of the caloric scale; the more men in the group the fewer the calories. When women ate in all-female groups, their food was significantly higher in calories. "Eating is a social activity," says Young. "In university cafeterias people select their food before they are seated and perhaps before they know with whom they will eat. Given the observed differences it seems likely that social groupings were anticipated at the time of food selection." Young is not surprised by the findings. The diet industry targets female consumers and product advertisements typically depict very slim models rather than average-sized or overweight female models, she says, so food choices appear to be weighed against how other perceive them. In other words, smaller, healthier portions are seen as more feminine, and women might believe that if they eat less they will be considered more attractive to men. "It is possible that small food portions signal attractiveness, and women conform, whether consciously or unconsciously, to small meals in order to be seen as more attractive," says Young. As for men's food selections, the study showed that men were neither substantially affected by the number of nor the gender of their dining companions. From McMaster University (2009, August 10). What You Eat Depends On With Whom You Eat. ScienceDaily. Retrieved August 13, 2009, from http://www.sciencedaily.com /releases/2009/08/090805114616.htm
  9. 9. Binge Drinkers Have A Disconnect Between Assessing Their Driving Abilities And Reality ScienceDaily (May 12, 2008) — While many people believe that alcohol-impaired (AI) drivers are usually alcoholics, in fact, 80 percent of AI incidents are caused by binge drinkers. A recent study conducted among college students has found that binge drinkers, even when legally intoxicated, nonetheless believe they having adequate driving abilities. "Binge drinkers are individuals who, when they drink, typically drink to get drunk," explained Cecile A. Marczinski, assistant professor in the department of psychology at Northern Kentucky University and first author of the study. "Binge drinkers are often young individuals, like college students, who are drinking irresponsibly and most of them are not alcohol dependent." College students, as a population, are most likely to binge drink, Marczinski added. "Binge drinking is widespread on college campuses, with almost half of students reporting binge drinking," she said. "They are also particularly prone to AI driving. Thus, we needed to understand why a population that knows better than to engage in impaired driving still does. Participants in this study were 20 male and 20 female social-drinking college students (24 binge drinkers, 16 non-binge drinkers) between 21 and 29 years of age. All participants attended two sessions: one during which they received a moderate dose of alcohol (0.65 g/kg), and one during which they received a placebo. Following each session/dose, researchers measured the students' performance during a simulated driving task, and also measured their subjective responses, including ratings of sedation, stimulation and driving abilities. "After being given an intoxicating dose of alcohol, all of these individuals -- both binge and non-binge drinkers -- were very poor drivers when tested on a driving simulator," said Marczinski. "However, when all of the participants are asked to rate their driving ability, the binge drinkers reported that they had a greater ability to drive compared to the non-binge drinkers." The authors hypothesize that binge drinkers lack an "internal sedation cue" that allows an accurate assessment of their driving abilities after drinking. "Furthermore," said Marczinski, "the dose of alcohol we gave resulted in a blood alcohol concentration (BAC) of .08g percent, which is the legal limit for driving. If these binge drinkers had been driving and were stopped by police, they would have been prosecuted for impaired driving." Marczinski said that these findings might help policy and law makers understand why the standard message of "don't drive when your BAC reaches .08 or more" may be not be as straight forward to follow as one might think. "A BAC of .08 may feel differently depending on how much you typically drink," she said. "If you often drink to get drunk, as many young people do, you will be very bad at determining whether or not you should drive. Thus, prevention programs where college students are stopped leaving bars and given a breathalyzer reading may help many individuals learn what .08 feels like. In addition, we might also entertain a lower BAC limit for driving. Many European countries have had great success in decreasing impaired driving rates and related accidents by lowering their BAC limit to .05." There is some good news, however. "While a small portion of young binge drinkers may develop serious problems with alcohol, most of them will mature out of this behavior," she said. Alcoholism: Clinical & Experimental Research (2008, May 12). Binge Drinkers Have A Disconnect Between Assessing Their Driving Abilities And Reality. ScienceDaily. Retrieved August 13, 2009, from http://www.sciencedaily.com /releases/2008/05/080511190840.htmBottom of Form
  10. 10. Sampling Error • The discrepancy between a sample statistic and its population parameter is called sampling error. • Defining and measuring sampling error is a large part of inferential statistics.
  11. 11. Variables • A variable is a characteristic or condition that can change or take on different values. • Most research begins with a general question about the relationship between two variables for a specific group of individuals.
  12. 12. 4 Types of Measurement Scales 1. A nominal scale is an unordered set of categories identified only by name. Nominal measurements only permit you to determine whether two individuals are the same or different. 2. An ordinal scale is an ordered set of categories. Ordinal measurements tell you the direction of difference between two individuals.
  13. 13. 4 Types of Measurement Scales 3. An interval scale is an ordered series of equal-sized categories. Interval measurements identify the direction and magnitude of a difference. The zero point is located arbitrarily on an interval scale. 4. A ratio scale is an interval scale where a value of zero indicates none of the variable. Ratio measurements identify the direction and magnitude of differences and allow ratio comparisons of measurements.
  14. 14. Tutorial on Scales of Measurement http://courses.csusm.edu/soc201kb/level_of_measurement.htm
  15. 15. Another Way to Characterize Numbers • Discrete Variables: values can fall only on certain points on a scale (e.g., birth order) • Continuous Variables: potential values are infinite (e.g., length of time to read a passage)
  16. 16. Statistical Notation • X = score on a variable (e.g., IQ score of 110 would be X = 110), if there are two scores per participant then the second score is referred to as “Y” (e.g., Age) • ∑ (Greek sigma) read as “the sum of” – ∑ X = “sum of X” = add all the scores together – (∑ X)2 = “sum of X squared” = add all of the scores together and then square total – ∑ X2 = “sum of squared Xs” = square each score, then add the squared scores together – ∑ XY = “sum of X times Y” = multiply X and Y for each participant, then add the products together – ∑ X-2 = “sum of X – 2” = subtract 2 from each score, then add the difference together

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