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CASE STUDY 2: Which one of the following incorrectly characteristic that null hypothesis on the case study 2? A. A child is equally like to have a birth defect everywhere across Des Moines B. A child is equally likely to have a birth defect whether their family income is low or high C. The frequency of birth defects the same everywhere in Des Moines D. The likelihood of a birth defects s the same from neighbourhood to neighbourhood E. The probability of a birth defect is the same everywhere in Des Moines Answer: C Which is the Process under study? A. Process in which a birth defect comes to be recognized B. Process in which babies may born with a birth defect C. Process in which families with infants (with or without a birth defect) move into Des Moines D. Process in which families with infants (with or without a birth defect) move out od Des Moines E. Process in which families with infants (with our without a birth defect) relocate within Des Moines Answer: B Which one of the following best describes the author’s objective? A. Explore whether there are any differences in the frequency of birth defects across Des Moines B. Explore whether there are substantial differences in the frequency of birth defects across Des Moines C. Test hypothesis that environmental conditions (e.g. deprivation) affect likelihood of birth defects D. Test hypothesis that social conditions (e.g. deprivation) affect likelihood of birth defects E. Test hypothesis that environmental and/or social conditions affect likelihood of birth defect Answer: B In the case study, what is a lattice point? A. An intersection of two streets B. Centroid of a census tract C. Location of a live birth; home address of mother D. Location of a birth defect: current address E. Systematic set off (regularly-spaced) points Answer: E Which one of the following does NOT describe accurately what was done in this case study?

A. Select lattice points spaced regularly at 0.5 mile interval s across city of Des Moines B. At each lattice point, draw a circle of radius at 0.4 miles C. Within each circle, find the total number of live births; discard lattice point if fewer than 40 D. Within each circle, find the corresponding total number of birth defects registered E. Estimate likelihood at lattice point as ratio of total birth defects to total live births in the circle Answer: C In its use of Monte Carlo simulation, what question do the authors NOT attempt to answer? A. Can we exclude the possibility of being incorrect in rejecting the null hypothesis? B. Can we find the probability of having made a mistake in rejecting the null hypothesis? C. How do we get from observed frequency to unobserved probability (likelihood) of birth defect? D. How do we rule out chance as an explanation of variation I estimated likelihood? E. When we estimate likelihood, how important is chance? Answer: A CASE STUDY 3: 1. The authors list several reasons for choosing Seattle WA as their study area. Which one of the following was NOT a reason listed A. Crime rate in Seattle has been rising in recent years B. Seattle data are publicly available C. Seattle has detailed data on criminal activity over long period of time D. Seattle is a slow growing city E. Seattle is a typical city of its size Answer: A 2. Which one of the following assertions about Case Study 3 is incorrect? A. An observation is a street segment B. At each lattice point across Seattle, the likelihood of a trajectory category is determined by kemel estimation C. Each observation is assigned to one of three overall trajectories categories D. In total, there were 1,490,725 observations in Case Study 3 E. The trajectory of police Incident Reports – from 1989 to 2002- is calculated for each observation Answer: D 3. There are similarities between Case Study 2 (Rushton & Lolonis) and Case Study 3 (Weisburd et al), which one of the following is incorrect?

A. Both studies do a spatial join B. Both studies draw a circle of fixed radius to estimate a likelihood in the vicinity of each lattice point C. Both studies estimate a likelihood surface D. Both studies use a systematic sample (lattice points) at which to estimate this likelihood E. Both studies use overlapping circles Answer: A 4. Of the significant differences between Case Study 2 and Case Study 3, which of the following is incorrect? A. Case Study 2 treats data as cross sectional while Case Study 3 treats data as time series B. Case Study 2 treats all occurrences within circle as equally-weighted; Case Study 3 weights C. Case Study 3 uses a smudge map to describe its findings whereas Case Study 2 uses contour lines D. In Case Study 2, there are two possible outcomes while in Case Study 3, there are three possible outcomes E. Case Study 2 uses Monte Carlo simulation while Case Study 3 does not. Answer: C CASE STUDY 4: Key point: K-function 1. In the Cincinnati metropolitan area in 1976, in terms of what explanation characteristic (X) does Barff NOT use to explain clustering (Y) of manufacturers? A. Capital intensity B. Central city versus suburban C. Job shop versus line flow D. Labor intensive versus capital intensive E. Mover versus non-mover Answer: B 2. Which one of the following assertions about the author’s application of the K function method is NOT entirely correct? A. Divide the sampled 518 manufacturing establishment into 2 groups B. At the site of sampled establishment in a group, draw a circle of radius D (miles) C. Court the proportion-K(D)-of other sampled establishments, from the group, within this circle D. At D sufficiently small, K(D) is near 0; at D sufficiently large, K(D) is near 1. E. Calculate the arithmetic average, K(D), over all the K(D) within the group Answer: A 3. Which one of the following assertions is most clearly correct? A. Author does not exclude any sampled establishments B. Author does take into account aggregation effects C. Author does take into account edges effects

D. Author uses a spatial join E. With K function, author is able to model profitability and/or survivorship of manufacturing establishments Answer: B 4. In what one respect might Rushton & Lolonis NOT be critical of the study by Barff A. Barff does not calculate a likelihood surface B. Barff does not estimate the effect of sampling variability C. Barff does not geocode manufacturing establishments correctly D. Barff does not consider how neighborhood or district affects a manufacturer’s choice of site E. Barff’s sample is small and limited to one year Answer: D CASE STUDY 5: In case study 5, which of the following is NOT seen to be central to public health surveillance? A. Risk of morbidity or mortality by education B. Risk of morbidity or mortality by ethnicity/ race C. Risk of morbidity or mortality by income D. Risk of morbidity or mortality by occupation E. Risk of morbidity or mortality by wealth Answer: B How do the author measure risk? A. By calculating the proportion ill or deaths in specified districts (geographic areas) B. By drawing a circle at each regularly spaced lattice point and calculating proportion ill or deaths C. By drawing a circle at each regularly spaced lattice point and estimating a kerned density function D. By estimating a K-function at selected location to see which radius [d] best E. By following individuals over time to see who becomes ill or dies Answer: A Which one of the following best describes the approach to geographic scale in this case study? A. Relationship between health outcome and socioeconomic status is same at all geographic scales B. Relationships between health outcome and socioeconomic status is not same at all geographic scales C. The effect of geographic scale I best taken into account using a kernel function D. The effect of geographic scale is best taken into account using a k-function E. There is no relationship between health outcome and socioeconomic status at any geographic scale Answer: B

Which one of he following steps is not undertaken in this case study? A. Geocode person is SEER and deaths to block group, census tract and zip code. Numerator is count by page B. Denominator is census count of persons by age in area C. Calculate age-standardized (adjusted) cancer incidence and mortality rate D. Estimate surface for age-adjusted cancer incidence and mortality rates over MA and RI study area E. Calculate cut points for area-based deprivation measure (e.g. quintiles) and then gradient (IRR) as ratio of rates: target group to least-deprived group Answer: D CASE STUDY 6 What can we most correctly conclude about the map of San Francisco census tracts presented in Figure 2? A. The map datum appears to be NAD83 B. The map appears to be a conic projection C. The map appears to be a UTM projection D. The scale of the map appears to be 1:100000 Answer: C How do the authors measure distance from the Sutro tower? A. Cartesian distance B. Economic distance (travel cost) C. Great circle route distance D. Manhattan (rectangular) distance E. Network distance (distance along existing streets) Answer: A Which one of the following data items was NOT assembled for this case study? A. Centroid (coordinates) of each Census Tract in San Francisco in 1980 B. Location (coordinates) of Sutro Tower C. Total population of Caucasian Children by Census Tract in San Francisco in 1980 D. Home address of each Caucasian child cancer patient in the San Francisco SEER, 1973-1988 E. Residential history (previous home addresses) of each Caucasian child cancer patient in the San Francisco SEER, 1973-1988 Answer: E How do the authors calculate the centroid of a census tract? A. Mean center (center of gravity) B. Medium canter (Simple centroid) C. Weighted mean center D. None of the above E. Authors do not explain calculation of centroid

Answer: E For a statistical test significant at the 9% confidence level, which one of the following world NOT be true? A. According to this test, we would be correct 19 times out of 20 to reject H B. For this test, the probability of Type 1 error (reject H, when H, is the fact true) is not more than 5% C. In this test result, sample size is not large enough to true out of sampling variability at this level of confidence D. The p-value for this test is no more than 0.05 E. The probability of Type II error (accept H, when H is true) is generally not calculate if H is inexact Answer: C This case study is similar to Rushton & Lolonis in that both use Monte Carlo simulation. Which one of he following comparisons is NOT correct? A. Both studies estimate a likelihood (risk) surface across the study area B. Both studies generate a large number of simulated samples C. Both studies seek to calculate the likelihood that the observed sample has some characteristic D. Both studies simulate data on the assumption Ho definitively is true E. In nether study can we use simulation definitively reject Ho Answer: A In comparing “relative risk analysis” in this case study to the birth defect study (Rushton & Lolonis), which one of the following is correct? A. Both case studies use a registry (birth defects or child cancer cases) B. Both imagine a risk that, under the null hypothesis, is the same across the study area (city or country) C. Both case studies geocode address in the registry using a street network file D. Both calculate a risk by taking a ratio of registry records to child births locally Answer: C CASE STUDY 7: 1. The authors seek to explain the variation in FFRD across New Orleans. What is FFRD? A. Growth rate of fast food outlets locally over the last decade B. Number of fast food outlets locally C. Ratio of fast food outlets to all restaurants locally D. Radio of fast food outlets to land area locally E. Radio of fast food outlets to population locally Answer: D 2. In Case Study 7, what do the authors seek to do? A. Describe the local variations in FFRD across New Orleans B. Explain the local variations in FFRD across New Orleans C. Predict the local variations in FFRD across New Orleans

D. Simulate the local variations in FFRD across New Orleans E. Control the local variations in FFRD across New Orleans Answer: C 3. In Case Study 7, what statistical method is used by the authors? A. Fit a statistical surface of FFRD across New Orleans B. Use difference of means to compare FFRD for some residents of New Orleans with that for others C. Use relative risk to compare FFRD some areas of New Orleans with other areas D. Use K-function to explore clustering of fast food outlets across New Orleans E. Use multiple regression to associate variations in FFRD with local social characteristics Answer: E CASE STUDY 8: In this case study, what is a property parcel? A. Any house, apartment, mobile home, or other residential structure B. Any parcel of land for which property tax is assessed C. Any residential property on which property tax is assed D. Any site of a business Answer: C For each property parcel included as an observation (trial), what is the author’s dependent variable (Y)? A. Average blood lead level of all tested children at that address B. Blood lead level of child at that property with highest tested BLL C. Blood lead level of tested child at that property with highest tested BLL truncated from below at 1 ppm D. Logarithm of the truncated blood lead level of child at that property with highest tested BLL Answer: D The authors calculate six explanatory (X) variables (median income, percent black, percent children in poverty, percent center-occupied, percent single parent, and year built) each at a particular geographic scale. Which geographic scale is NOT used? A. City block B. Block group C. Census tract D. Tax parcel Answer: C Once the Y data are geocoded how do the authors spatially join their Y data with their X data? A. Adjacency B. Nearest neighbour C. Point in-polygon D. Roving window

Answer: C The authors calculate 6 explanatory (X) variables (median income, percent block, and percent children in poverty. The statistical model in Table 4 includes only three X variables: year built median income, and percent black). Why did authors drop the other three: i.e. percent children property, percent renter-occupied, and percent single parent? A. Data for the latter there were unavailable B. Data for the latter three were unreliable C. Latter three did not contribute substantially to model fit in Table 4 D. Latter three were thought to be unimportant in understanding In(BLL) Answer: C What do authors seek to explain, predict, or replicate? A. Variation in blood lead level from child to child across sample B. Variation in blood lead level from property to property across sample C. Variation in In(BLL) from child to child across sample D. Variation in In(BLL) from country to country across sample E. Variation in In(BLL) from property to property across sample Answer: E CASE STUDY 9: In this case study, what is a trial on the authors’ statistical experiment? A. Alcohol establishment B. Block group C. Census tract D. City block E. Police precinct Answer: B In terms of which variable do to the authors seek to explain variation? A. Alcohol establishment outlet density B. Percent population moved (1985-90) C. Proportion population aged 12-17 years D. Welfare rate E. Violent crime rate Answer: E CASE STUDY 10: What do the authors seek to explain, predict, or reproduce? A. Variation in food desert status from school district to school district B. Variation in frequency of incomplete kitchens from school district to school district C. Variation in frequency of mobile homes from school district to school district D. Variation in household income from school district to school district E. Variation in obesity from school district to school district

Answer: E For each of the 92 rural school district in Pennsylvania in 1999 (and 2001), what is the dependent variable (Y) to be explain in Table 5 (and 6)? A. Percent of children in school who are overweight B. Proportion of children in school who are overweigh C. Percentage of children in school whose weight exceeds healthy D. Proportion of children in schools whose weight exceeds healthy E. Percent of children in school whose weight is not healthy Answer: C For 1999, what is the average level of Y about which the author then calculates the variation for each school district? A. 15.98% B. 17.91% C. 32.38% D. 33.34% E. 36.57% Answer: D In the steps taken to determine a food desert school district, which one of the following is incorrect? A. Authors identity each zip code in Pennsylvania that has at least one large grocery store (5o or ore employees) Answer: A Answer: B Answer: D Answer: E Answer: C...