CHAPTER 10: FUNCTIONAL DEPENDENCIES AND NORMALIZATION FOR RELATIONAL DATABASES


CHAPTER 10: FUNCTIONAL DEPENDENCIES AND NORMALIZATION FOR RELATIONAL DATABASES

 

Answers to Selected Exercises

 

15.19 Suppose we have the following requirements for a university database that is

used to keep track of students transcripts:

 

(a) The university keeps track of each student’s name (SNAME), student number

(SNUM), social security number (SSSN), current address (SCADDR) and phone

(SCPHONE), permanent address (SPADDR) and phone (SPPHONE), birthdate

(BDATE), sex (SEX), class (CLASS) (freshman, sophomore, …, graduate),

major department (MAJORDEPTCODE), minor department (MINORDEPTCODE)

(if any), and degree program (PROG) (B.A., B.S., …, Ph.D.). Both ssn and

student number have unique values for each student.

 

(b) Each department is described by a name (DEPTNAME), department code

(DEPTCODE), office number (DEPTOFFICE), office phone (DEPTPHONE), and

college (DEPTCOLLEGE). Both name and code have unique values for each

department.

 

(c) Each course has a course name (CNAME), description (CDESC), code number

(CNUM), number of semester hours (CREDIT), level (LEVEL), and offering

department (CDEPT). The value of code number is unique for each course.

 

(d) Each section has an instructor (INSTUCTORNAME), semester (SEMESTER), year

(YEAR), course (SECCOURSE), and section number (SECNUM). Section numbers

distinguish different sections of the same course that are taught during the same

semester/year; its values are 1, 2, 3, …; up to the number of sections taught

during each semester.

 

(e) A transcript refers to a student (SSSN), refers to a particular section, and

grade (GRADE).

 

Design an relational database schema for this database application. First show all

the functional dependencies that should hold among the attributes. Then, design

relation schemas for the database that are each in 3NF or BCNF. Specify the key

attributes of each relation. Note any unspecified requirements, and make

appropriate assumptions to make the specification complete.

 

 

10.18 Prove or disprove the following inference rules for functional dependencies. A

proof can be made either by a proof argument or by using inference rules IR1 through IR3. A disproof should be done by demonstrating a relation instance that satisfies the conditions and functional dependencies in the left hand side of the inference rule but do not

satisfy the conditions or dependencies in the right hand side.

 

(a) {W ->Y, X ->Z} |= {WX ->Y }

 

(b) {X ->Y} and Z subset-of Y |= { X ->Z }

 

(c) { X ->Y, X ->W, WY ->Z} |= {X ->Z}

 

(d) {XY ->Z, Y ->W} |= {XW ->Z}

 

(e) {X ->Z, Y ->Z} |= {X ->Y}

 

(f) {X ->Y, XY ->Z} |= {X ->Z}

 

 

10.19 Consider the following two sets of functional dependencies F= {A ->C, AC ->D,

E ->AD, E ->H} and G = {A ->CD, E ->AH}. Check whether or not they are

equivalent.

 

 

10.22 What update anomalies occur in the EMP_PROJ and EMP_DEPT relations of

Figure 14.3 and 14.4?

 

 

10.23 In what normal form is the LOTS relation schema in Figure 10.11(a) with the

respect to the restrictive interpretations of normal form that take only the

primary key into account? Will it be in the same normal form if the general

definitions of normal form were used?

 

Answer:

 

If we only take the primary key into account, the LOTS relation schema in Figure 14.11

(a) will be in 2NF since there are no partial dependencies on the primary key .

However, it is not in 3NF, since there are the following two transitive dependencies on

the primary key:

PROPERTY_ID# ->COUNTY_NAME ->TAX_RATE, and

PROPERTY_ID# ->AREA ->PRICE.

Now, if we take all keys into account and use the general definition of 2NF and 3NF, the

LOTS relation schema will only be in 1NF because there is a partial dependency

COUNTY_NAME ->TAX_RATE on the secondary key {COUNTY_NAME, LOT#}, which

violates 2NF.

 

10.24 Prove that any relation schema with two attributes is in BCNF.

 

 

10.25 Why do spurious tuples occur in the result of joining the EMP_PROJ1 and

EMPLOCS relations of Figure 14.5 (result shown in Figure 14.6)?

 

 

10.26 Consider the universal relation R = {A, B, C, D, E, F, G, H, I} and the set of

functional dependencies F = { {A, B} -> {C}, {A} -> {D, E}, {B} -> {F}, {F} ->

{G, H}, {D} -> {I, J} }. What is the key for R? Decompose R into 2NF, then 3NF

relations.

 

 

10.27 Repeat exercise 10.26 for the following different set of functional dependencies

G = { {A, B} -> {C}, {B, D} -> {E, F}, {A, D} -> {G, H}, {A} -> {I}, {H} -> {J} }.

 

14.26, starting with the following relation R:

R = {A, B, D, C, E, F, G, H, I}

The first-level partial dependencies on the key (which violate 2NF) are:

{A, B} -> {C, I}, {B, D} -> {E, F}, {A, D}+ -> {G, H, I, J}

Hence, R is decomposed into R1, R2, R3, R4 (keys are underlined):

R1 = {A, B, C, I}, R2 = {B, D, E, F}, R3 = {A, D, G, H, I, J}, R4 = {A, B, D}

Additional partial dependencies exist in R1 and R3 because {A} -> {I}. Hence, we remove

{I} into R5, so the following relations are the result of 2NF decomposition:

R1 = {A, B, C}, R2 = {B, D, E, F}, R3 = {A, D, G, H, J}, R4 = {A, B, D}, R5 = {A, I}

Next, we check for transitive dependencies in each of the relations (which violate 3NF).

Only R3 has a transitive dependency {A, D} -> {H} -> {J}, so it is decomposed into R31

and R32 as follows:

R31 = {H, J}, R32 = {A, D, G, H}

The final set of 3NF relations is {R1, R2, R31, R32, R4, R5}

 

10.28 Solution to come

 

10.29 Given relation R(A,B,C,D,E) with dependencies

C.AB

E.CD

B.DE

is AB a candidate key?

is ABD a candidate key?

 

 

10.30 Consider the relation R, which has attributes that hold schedules of courses and

sections at a university; R = {CourseNo, SecNo, OfferingDept, CreditHours,

CourseLevel, InstructorSSN, Semester, Year, Days_Hours, RoomNo,

NoOfStudents}. Suppose that the following functional dependencies hold on R:

{CourseNo} -> {OfferingDept, CreditHours, CourseLevel}

{CourseNo, SecNo, Semester, Year} ->

{Days_Hours, RoomNo, NoOfStudents, InstructorSSN}

{RoomNo, Days_Hours, Semester, Year} -> {InstructorSSN, CourseNo, SecNo}

Try to determine which sets of attributes form keys of R. How would you

normalize this relation?

 

Answer:

 

10.31 Consider the following relations for an order-processing application database at ABC, Inc.

 

ORDER (O#, Odate, Cust#, Total_amount)

ORDER-ITEM (O#, I#, Qty_ordered, Total_price, Discount%)

 

Assume that each item has a different discount. The Total_price refers to one item, Odate is the date on which the order was placed, and the Total_amount is the amount of the order. If we apply a natural join on the relations Order-Item and Order in this database, what does the resulting relation schema look like? What will be its key? Show the FDs in this resulting relation. Is it in 2NF? Is it in 3NF? Why or why not? (State any assumptions you make.)

 

O# .Total_amount

It is not in 2NF, as attributes Odate, Cut#, and Total_amount are only partially

dependent on the primary key, O#I#

Nor is it in 3NF, as a 2NF is a requirement for 3NF.

 

 

10.32 Consider the following relation:

CAR_SALE(Car#, Date_sold, Salesman#, Commision%, Discount_amt

Assume that a car may be sold by multiple salesmen and hence {CAR#, SALESMAN#} is the primary key. Additional dependencies are:

Date_sold ->Discount_amt

and

Salesman# ->commission%

Based on the given primary key, is this relation in 1NF, 2NF, or 3NF? Why or why not? How would you successively normalize it completely?

 

 

10.33 Consider the following relation for published books:

BOOK (Book_title, Authorname, Book_type, Listprice, Author_affil, Publisher)

Author_affil referes  to the affiliation of the author. Suppose the following dependencies exist:

Book_title -> Publisher, Book_type

Book_type -> Listprice

Author_name -> Author-affil

 

(a) What normal form is the relation in? Explain your answer.

(b) Apply normalization until you cannot decompose the relations further. State the reasons behind each decomposition.

 

 

(a)The key for this relation is Book_title,Authorname. This relation is in 1NF and not in

2NF as no attributes are FFD on the key. It is also not in 3NF.

 

(b) 2NF decomposition:

Book0(Book_title, Authorname)

Book1(Book_title, Publisher, Book_type, Listprice)

Book2(Authorname, Author_affil)

This decomposition eliminates the partial dependencies.

3NF decomposition:

Book0(Book_title, Authorname)

Book1-1(Book_title, Publisher, Book_type)

Book1-2(Book_type, Listprice)

Book2(Authorname, Author_affil)

This decomposition eliminates the transitive dependency of Listprice

 

 

 

 

 

 

    • 8 years ago

    Statistics Homework


    4.2 Identify the parameter, Part II. For each of the following situations, state whether the

    parameter of interest is a mean or a proportion.

     

    (a) A poll shows that 64% of Americans personally worry a great deal about federal spending and the budget deficit.

    (b) A survey reports that local TV news has shown a 17% increase in revenue between 2009 and 2011 while newspaper revenues decreased by 6.4% during this time period.

    (c) In a survey, high school and college students are asked whether or not they use geolocation

    services on their smart phones.

    (d) In a survey, internet users are asked whether or not they purchased any Groupon coupons.

    (e) In a survey, internet users are asked how many Groupon coupons they purchased over the last year.

     

    4.4 Heights of adults. Researchers studying anthropometry collected body girth measurements

    and skeletal diameter measurements, as well as age, weight, height and gender, for 507 physically

    active individuals. The histogram below shows the sample distribution of heights in centimeters.

     

    (a) What is the point estimate for the average height of active individuals? What about the

    median?

    (b) What is the point estimate for the standard deviation of the heights of active individuals?

    What about the IQR?

    (c) Is a person who is 1m 80cm (180 cm) tall considered unusually tall? And is a person who is

    1m 55cm (155cm) considered unusually short? Explain your reasoning.

    (d) The researchers take another random sample of physically active individuals. Would you

    expect the mean and the standard deviation of this new sample to be the ones given above.

    Explain your reasoning.

    (e) The samples means obtained are point estimates for the mean height of all active individuals,

    if the sample of individuals is equivalent to a simple random sample. What measure do we use

    to quantify the variability of such an estimate? Compute this quantity using the data from

    the original sample under the condition that the data are a simple random sample.

     

    4.6 Chocolate chip cookies. Students are asked to count the number of chocolate chips in 22

    cookies for a class activity. They found that the cookies on average had 14.77 chocolate chips with

    a standard deviation of 4.37 chocolate chips.

    (a) Based on this information, about how much variability should they expect to see in the mean

    number of chocolate chips in random samples of 22 chocolate chip cookies?

    (b) The packaging for these cookies claims that there are at least 20 chocolate chips per cookie.

    One student thinks this number is unreasonably high since the average they found is much

    lower. Another student claims the di_erence might be due to chance. What do you think?

     

    4.8 Mental health. Another question on the General Social Survey introduced in Exercise 4.7

    is \For how many days during the past 30 days was your mental health, which includes stress,

    depression, and problems with emotions, not good?” Based on responses from 1,151 US residents,

    the survey reported a 95% confidence interval of 3.40 to 4.24 days in 2010.

    (a) Interpret this interval in context of the data.

    (b) What does a 95% confidence level mean in this context?

    (c) Suppose the researchers think a 99% confidence level would be more appropriate for this

    interval. Will this new interval be smaller or larger than the 95% confidence interval?

    (d) If a new survey asking the same questions was to be done with 500 Americans, would the

    standard error of the estimate be larger, smaller, or about the same. Assume the standard

    deviation has remained constant since 2010.

     

    4.10 Confidence levels. If a higher con_dence level means that we are more confident about

    the number we are reporting, why don’t we always report a confidence interval with the highest

    possible confidence level?


    4.12 Thanksgiving spending, Part I. The 2009 holiday retail season, which kicked off  on November 27, 2009 (the day after Thanksgiving), had been marked by somewhat lower self-reported consumer spending than was seen during the comparable period in 2008. To get an estimate of consumer spending, 436 randomly sampled American adults were surveyed. Daily consumer spending for the six-day period after Thanksgiving, spanning the Black Friday weekend and Cyber Monday, averaged $84.71. A 95% confidence interval based on this sample is ($80.31, $89.11).  Determine whether the following statements are true or false, and explain your reasoning.

    (a) We are 95% confident  that the average spending of these 436 American adults is between

    $80.31 and $89.11.

    (b) This confidence interval is not valid since the distribution of spending in the sample is right

    skewed.

    (c) 95% of such random samples would have a sample mean between $80.31 and $89.11.

    (d) We are 95% confident that the average spending of all American adults is between $80.31 and

    $89.11.

    (e) A 90% confidence interval would be narrower than the 95% confidence interval since we don’t

    need to be as sure about capturing the parameter.

    (f) In order to decrease the margin of error of a 95% confidence interval to a third of what it is

    now, we would need to use a sample 3 times larger.

    (g) The margin of error for the reported interval is 4.4.

     


    4.14 Age at first marriage, Part I. The National Survey of Family Growth conducted by the

    Centers for Disease Control gathers information on family life, marriage and divorce, pregnancy,

    infertility, use of contraception, and men’s and women’s health. One of the variables collected on

    this survey is the age at first marriage. The histogram below shows the distribution of ages at

    first marriage of 5,534 randomly sampled women between 2006 and 2010. The average age at first

    marriage among these women is 23.44 with a standard deviation of 4.72

     

    Estimate the average age at _rst marriage of women using a 95% confidence interval, and interpret

    this interval in context. Discuss any relevant assumptions.

     

    4.16 Identify hypotheses, Part II. Write the null and alternative hypotheses in words and

    using symbols for each of the following situations.

    (a) Since 2008, chain restaurants in California have been required to display calorie counts of

    each menu item. Prior to menus displaying calorie counts, the average calorie intake of diners

    at a restaurant was 1100 calories. After calorie counts started to be displayed on menus, a nutritionist collected data on the number of calories consumed at this restaurant from a random sample of diners. Do these data provide convincing evidence of a difference in the average calorie intake of a diners at this restaurant?

    (b) Based on the performance of those who took the GRE exam between July 1, 2004 and June 30, 2007, the average Verbal Reasoning score was calculated to be 462. In 2011 the average verbal score was slightly higher. Do these data provide convincing evidence that the average GRE Verbal Reasoning score has changed since 2004?

    4.18 Age at first marriage, Part II. Exercise 4.14 presents the results of a 2006 – 2010 survey showing that the average age of women at first marriage is 23.44. Suppose a researcher believes

    that this value has increased in 2012, but he would also be interested if he found a decrease. Below

    is how he set up his hypotheses. Indicate any errors you see.

     

     

    4.20 Thanksgiving spending, Part II. Exercise 4.12 provides a 95% confidence interval for the

    average spending by American adults during the six-day period after Thanksgiving 2009: ($80.31,

    $89.11).

    (a) A local news anchor claims that the average spending during this period in 2009 was $100.

    What do you think of this claim?

    (b) Would the news anchor’s claim be considered reasonable based on a 90% confidence interval?

    Why or why not?

     

    4.22 Gifted children, Part I. Researchers investigating characteristics of gifted children col-

    lected data from schools in a large city on a random sample of thirty-six children who were identified as gifted children soon after they reached the age of four. The following histogram shows the distribution of the ages (in months) at which these children first counted to 10 successfully. Also provided are some sample statistics.

    (a) Are conditions for inference satisfied?

    (b) Suppose you read on a parenting website that children first count to 10 successfully when they

    are 32 months old, on average. Perform a hypothesis test to evaluate if these data provide

    convincing evidence that the average age at which gifted children first count to 10 successfully

    is different than the general average of 32 months. Use a significance level of 0.10.

    (c) Interpret the p-value in context of the hypothesis test and the data.

    (d) Calculate a 90% confidence interval for the average age at which gifted children first count to

    10 successfully. (e) Do your results from the hypothesis test and the confidence interval agree? Explain.

     

    4.24 Gifted children, Part II. Exercise 4.22 describes a study on gifted children. In this study, along with variables on the children, the researchers also collected data on the mother’s and father’s IQ of the 36 randomly sampled gifted children. The histogram below shows the distribution of mother’s IQ. Also provided are some sample statistics.

     

     

    (a) Perform a hypothesis test to evaluate if these data provide convincing evidence that the average IQ of mothers of gifted children is different than the average IQ for the population at large, which is 100. Use a significance level of 0.10.

    (b) Calculate a 90% confidence interval for the average IQ of mothers of gifted children.

    (c) Do your results from the hypothesis test and the confidence interval agree? Explain.


    4.26 Find the sample mean. You are given the following hypotheses:

    We know that the sample standard deviation is 10 and the sample size is 65. For what sample

    mean would the p-value be equal to 0.05? Assume that all conditions necessary for inference are

    satisfied.

     

    4.28 Testing for food safety. A food safety inspector is called upon to investigate a restaurant with a few customer reports of poor sanitation practices. The food safety inspector uses a hypothesis testing framework to evaluate whether regulations are not being met. If he decides the restaurant is in gross violation, its license to serve food will be revoked.

    (a) Write the hypotheses in words.

    (b) What is a Type 1 error in this context?

    (c) What is a Type 2 error in this context?

    (d) Which error is more problematic for the restaurant owner? Why?

    (e) Which error is more problematic for the diners? Why?

    (f) As a diner, would you prefer that the food safety inspector requires strong evidence or very

    strong evidence of health concerns before revoking a restaurant’s license? Explain your reasoning.

     

    4.30 Car insurance savings, Part I. A car insurance company advertises that customers switching to their insurance save, on average, $432 on their yearly premiums. A market researcher at a competing insurance discounter is interested in showing that this value is an overestimate

    so he can provide evidence to government regulators that the company is falsely advertising their

    prices. He randomly samples 82 customers who recently switched to this insurance and finds an

    average savings of $395, with a standard deviation of $102.

    (a) Are conditions for inference satisfied?

    (b) Perform a hypothesis test and state your conclusion.

    (c) Do you agree with the market researcher that the amount of savings advertised is an overestimate? Explain your reasoning.

    (d) Calculate a 90% confidence interval for the average amount of savings of all customers who

    switch their insurance.

    (e) Do your results from the hypothesis test and the confidence interval agree? Explain.

     

     

    4.32 Speed reading, Part I. A company offering online speed reading courses claims that students who take their courses show a 5 times (500%) increase in the number of words they can read in a minute without losing comprehension. A random sample of 100 students yielded an average increase of 415% with a standard deviation of 220%. Is there evidence that the company’s claim is false?

    (a) Are conditions for inference satisfied?

    (b) Perform a hypothesis test evaluating if the company’s claim is reasonable or if the true average improvement is less than 500%. Make sure to interpret your response in context of the hypothesis test and the data. Use α= 0:025.

    (c) Calculate a 95% confidence interval for the average increase in the number of words students

    can read in a minute without losing comprehension.

    (d) Do your results from the hypothesis test and the confidence interval agree? Explain.

     

    4.34 Ages of pennies, The histogram below shows the distribution of ages of pennies at a bank.

    The mean age of the pennies is 10.44 years with a standard deviation of 9.2 years. Using the Central Limit Theorem, calculate the means and standard deviations of the distribution of the mean from random samples of size 5, 30, and 100.  Comment on whether the sampling distributions shown  agree with the values you compute.

     

    4.36 Identify distributions, Part II. Four plots are presented below. The plot at the top is a distribution for a population. The mean is 60 and the standard deviation is 18. Also shown

    below is a distribution of (1) a single random sample of 500 values from this population, (2) a

    distribution of 500 sample means from random samples of each size 18, and (3) a distribution of

    500 sample means from random samples of each size 81. Determine which plot (A, B, or C) is

    which and explain your reasoning.

    4.38 Stats final scores. Each year about 1500 students take the introductory statistics course at a large university. This year scores on the final exam are distributed with a median of 74 points,

    a mean of 70 points, and a standard deviation of 10 points. There are no students who scored

    above 100 (the maximum score attainable on the final) but a few students scored below 20 points.

    (a) Is the distribution of scores on this final exam symmetric, right skewed, or left skewed?

    (b) Would you expect most students to have scored above or below 70 points?

    (c) Can we calculate the probability that a randomly chosen student scored above 75 using the

    normal distribution?

    (d) What is the probability that the average score for a random sample of 40 students is above

    75?

    (e) How would cutting the sample size in half affect the standard error of the mean?

     

     

     

     

     

     

     

    4.40 CFLs. A manufacturer of compact fluorescent light bulbs advertises that the distribution of  the lifespans of these light bulbs is nearly normal with a mean of 9,000 hours and a standard deviation of 1,000 hours.

    (a) What is the probability that a randomly chosen light bulb lasts more than 10,500 hours?

    (b) Describe the distribution of the mean lifespan of 15 light bulbs.

    (c) What is the probability that the mean lifespan of 15 randomly chosen light bulbs is more than

    10,500 hours?

    (d) Sketch the two distributions (population and sampling) on the same scale.

    (e) Could you estimate the probabilities from parts (a) and (c) if the lifespans of light bulbs had

    a skewed distribution?

     

    4.42 Spray paint. Suppose the area that can be painted using a single can of spray paint is slightly variable and follows a nearly normal distribution with a mean of 25 square feet and a standard deviation of 3 square feet.

    (a) What is the probability that the area covered by a can of spray paint is more than 27 square

    feet?

    (b) Suppose you want to spray paint an area of 540 square feet using 20 cans of spray paint. On

    average, how many square feet must each can be able to cover to spray paint all 540 square

    feet?

    (c) What is the probability that you can cover a 540 square feet area using 20 cans of spray paint?

    (d) If the area covered by a can of spray paint had a slightly skewed distribution, could you still

     

    calculate the probabilities in parts (a) and (c) using the normal distribution?

    • 9 years ago

    Calc lll, Need help


    I need help with this assignment, please include the steps of the solutions.

    Thank you 

    • 7 years ago
    • 30

    Finance Discussion Week 5

    Finance Discussion Week 5

    Assume you are the CFO of a medium-sized company and you are advising the CEO on some upcoming strategic initiatives that will have long-term implications. In other words, these are important decisions.

    For your initial discussion forum post, address the following questions posed by the CEO:

    · It appears we may need to raise more capital. Is expanding debt a good idea? Why or why not and should our given assets impact this decision?

    · In our economic environment, should we issue bonds, common stock, or preferred stock? What would be some pros and cons?

    · Or should we forego this immediate opportunity and buy back some of our outstanding common stock? What market conditions would make this a good move; what might be some pros and cons?

    · Should we issue a dividend, or should we retain cash in the company for future opportunities? How might this impact future growth? Are we obligated to pay our shareholders a dividend?

    Your initial response should be a minimum of 300 words. Students need to learn how to assess the perspectives of several scholars. Support your response with at least one scholarly and/or credible resource in addition to the text.

     

     

    Finance Discussion Week 5

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    International Business Week 5 Discussion 2

    International Business Week 5 Discussion 2

    The hiring proposal should address the following scenario:

    Your multinational company (MNC) is opening a new operations service hub in Shanghai and you are on the international HR Team putting together the hiring process for both transition team assignments and those that will be permanent positions in China. Initially, there will be 10 transition team and 10 local assignments. The Division Head for Asia Pacific has asked you to use a “Geocentric Approach” in preparing your hiring process. Research and share insights that address the following questions for your team:

    · What are some of the pros and cons of hiring host-country nationals (HCNs), third-country nationals (TCNs), or parent-country nationals (PCNs)?

    · Describe two strategies that would minimize expatriate failure.

    · Research and share data about current compensation systems in China (Shanghai specifically) and how compensation will impact the hiring process.

    · Research the practices of layoffs versus across-the-board pay cuts in China and share your findings.

    Your initial post should be 400 words. You should use at least two credible and recent sources

     

     

    International Business Week 5 Discussion 2

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    Preliminary Field & Laboratory Testing

    Preliminary Field & Laboratory Testing

     

    Handling and processing evidence is an integral component of crime scene management because it lays the foundation for everything the court must consider when weighing the admissibility of evidence. For the most part, the courts prefer testing being carried out in a laboratory setting. However, there are exceptions, such as times when an initial examination also yields valuable information. In this assignment, you will differentiate between testing that might be done on-scene versus in the laboratory, identify testing that might be subject to preliminary testing, as well as compare the different results yielded by preliminary field versus laboratory testing. Support your assignment with examples from this week’s required material(s) and/or a minimum of three other scholarly or credible resources and properly cite any references.

    Prior to beginning work on this assignment, please review the following:

    You are also strongly encouraged to review the list of recommended resources, as they may assist you with this assignment.

    In your assignment, address the following:

    • Identify what types of evidence might be subjected to preliminary or field testing.
    • Describe at least two types of testing that might be done on scene.
    • Differentiate between why some evidence can and should be subjected to preliminary testing on scene, while other types should not.
    • Explain how the on-scene test compares to laboratory testing.
    • Compare and contrast the results yielded by preliminary field versus laboratory testing.
    • Compare and contrast the admissibility of on-scene versus laboratory testing at trial.

    The Difference Between Preliminary Field and Laboratory Testing assignment

     

    Preliminary Field & Laboratory Testing

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