A researcher is examining the effect of neighborhood crime-watch efforts have on the crime rate in those neighborhoods, but he is not sure what direction the relationship might be; neighborhoods with high crime rates might have more crime watch efforts that are an attempt to address the high level of crime, or neighborhoods with high crime rates may have fewer crime watch efforts, which might explain why they have so much crime. The appropriate hypothesis test would be:

Study 2: Pill Appearance and Perceived Pain.    Does the shape or color of a pain pill influence its effectiveness?  Although logically it shouldn’t, whether we believe a drug will work does have a powerful effect on our perceptions (e.g., placebo effect).  In this experiment, 4 groups of adult patients were given the same amount of Advil after dental surgery for pain relief, but the color and shape of the pill varied.  Researchers hypothesized that an unusual shape or color would lead people to believe the pills were new and special and thus would expect them to be more effective than common round, white pills. Researchers also wanted to know if there is an interaction between shape and color Data Labels ShapePill {1=Round; 2=Diamond} ColorPill {1=White; 2=BlueGreen} Gender {0=Woman; 1=Man; 2=Nonbinary person) Descriptions of the Variables and Descriptive Statistics: Referring to the JASP output, and using sentences, present the descriptive statistics of each group: for example:…

A hypothetical study looks at the effect of drinking alcohol on health. Across all genders and age groups, people who do not drink tend to be healthier on average than people who do drink. However, people who drink regularly are on average healthier than those people who have recently stopped drinking. Is it reasonable to conclude that for the sake of health, we should not start drinking, but if we have already started drinking alcohol, it is healthier to continue and not to stop?

The success of an airline depends heavily on its ability to provide a pleasant customer experience. One dimension of customer service on which airlines compete is on-time arrival. The file LateFlights contains a sample of data from delayed flights showing the number of minutes each delayed flight was late for two different airlines, Delta and Southwest. Click on the datafile logo to reference the data. DATA file Southwest 120 29 67 89 115 a. Formulate the hypotheses that can be used to test for a difference between the population mean minutes late for delayed flights by these two airlines. 141 = population mean minutes late for delayed Delta flights 142 = population mean minutes late for delayed Southwest flights Ho 141 142 : Delta 113 36 113 82 26 - Select your answer - 0 Southwest 49 56 31 110 141 df = p-value = We - Select your answer-reject Ho. Delta 142 7 39 90 94 (rounded to 2 decimals) (rounded to 2 decimals) Southwest 66 131 125 26 31 H₂H₂ - Select your answer - 0 b. What is…

The phrase “Correlation does not equal causation” means:   Question 30 options:   there is no guarantee that a cause-and-effect relationship exists between two variables that are correlated.   there is only a 30% chance that a cause-and-effect relationship exists between two variables.   a cause-and-effect relationship only certainly exists when data are gathered in a specific way.   a cause-and-effect relationship can only exist with ratio-level variables.

The same media consultants decided to continue their investigation of the focal relationship between income and TV viewing habits. In order to confirm the existence of the focal relationship, they decided to control for immigration status by adding a variable measuring the number of each survey respondent's grandparents who were born outside the U.S. The researchers wonder if immigration background could influence both income and TV watching (but they hope this is not true, because it could invalidate the focal relationship). The researchers conduct a multivariate regression by adding a measure of number of grandparents born outside the U.S. to the regression equation presented in Equation 2 of Table 1. The results of the second regression equation are presented in Equation 2 of Table 1. Table 1. OLS Regression Coefficients Representing Influence of Income and Control Variables on Number of Hours of TV Watched per Day     Equation 1 Equation 2 Equation 3 Annual Income…