Obstetrics The following data are derived from the Monthly Vital Statistics Report (October 1999) issued by the National Center for Health Statistics [10]. These data are pertinent to livebirths only. Suppose that infants are classified as low birthweight if they have a birthweight <2500 g and as normal birthweight if they have a birthweight ≥2500 g. Suppose that infants are also classified by length of gestation in the following five categories: <28 weeks, 28–31 weeks, 32–35 weeks, 36 weeks, and ≥37 weeks. Assume the probabilities of the different periods of gestation are as given in Table 3.8. Also assume that the probability of low birthweight is .949 given a gestation of <28 weeks, .702 given a gestation of 28–31 weeks, .434 given a gestation of 32–35 weeks, .201 given a gestation of 36 weeks, and .029 given a gestation of ≥37 weeks. Table 3.8 Distribution of length of gestation What is the probability of having a length of gestation ≤36 weeks given that an infant is low birthweight?
Obstetrics The following data are derived from the Monthly Vital Statistics Report (October 1999) issued by the National Center for Health Statistics [10]. These data are pertinent to livebirths only. Suppose that infants are classified as low birthweight if they have a birthweight <2500 g and as normal birthweight if they have a birthweight ≥2500 g. Suppose that infants are also classified by length of gestation in the following five categories: <28 weeks, 28–31 weeks, 32–35 weeks, 36 weeks, and ≥37 weeks. Assume the probabilities of the different periods of gestation are as given in Table 3.8. Also assume that the probability of low birthweight is .949 given a gestation of <28 weeks, .702 given a gestation of 28–31 weeks, .434 given a gestation of 32–35 weeks, .201 given a gestation of 36 weeks, and .029 given a gestation of ≥37 weeks. Table 3.8 Distribution of length of gestation What is the probability of having a length of gestation ≤36 weeks given that an infant is low birthweight?
The following data are derived from the Monthly Vital Statistics Report (October 1999) issued by the National Center for Health Statistics [10]. These data are pertinent to livebirths only.
Suppose that infants are classified as low birthweight if they have a birthweight <2500 g and as normal birthweight if they have a birthweight ≥2500 g. Suppose that infants are also classified by length of gestation in the following five categories: <28 weeks, 28–31 weeks, 32–35 weeks, 36 weeks, and ≥37 weeks. Assume the probabilities of the different periods of gestation are as given in Table 3.8.
Also assume that the probability of low birthweight is .949 given a gestation of <28 weeks, .702 given a gestation of 28–31 weeks, .434 given a gestation of 32–35 weeks, .201 given a gestation of 36 weeks, and .029 given a gestation of ≥37 weeks.
Table 3.8 Distribution of length of gestation
What is the probability of having a length of gestation ≤36 weeks given that an infant is low birthweight?
The following are suggested designs for group sequential studies. Using PROCSEQDESIGN, provide the following for the design O’Brien Fleming and Pocock.• The critical boundary values for each analysis of the data• The expected sample sizes at each interim analysisAssume the standardized Z score method for calculating boundaries.Investigators are evaluating the success rate of a novel drug for treating a certain type ofbacterial wound infection. Since no existing treatment exists, they have planned a one-armstudy. They wish to test whether the success rate of the drug is better than 50%, whichthey have defined as the null success rate. Preliminary testing has estimated the successrate of the drug at 55%. The investigators are eager to get the drug into production andwould like to plan for 9 interim analyses (10 analyzes in total) of the data. Assume thesignificance level is 5% and power is 90%.Besides, draw a combined boundary plot (OBF, POC, and HP)
Please provide the solution for the attached image in detailed.
20 km, because
GISS
Worksheet 10
Jesse runs a small business selling and delivering mealie meal to the spaza shops.
He charges a fixed rate of R80, 00 for delivery and then R15, 50 for each packet of
mealle meal he delivers. The table below helps him to calculate what to charge
his customers.
10
20
30
40
50
Packets of mealie
meal (m)
Total costs in Rands
80
235
390
545
700
855
(c)
10.1.
Define the following terms:
10.1.1. Independent Variables
10.1.2. Dependent Variables
10.2.
10.3.
10.4.
10.5.
Determine the independent and dependent variables.
Are the variables in this scenario discrete or continuous values? Explain
What shape do you expect the graph to be? Why?
Draw a graph on the graph provided to represent the information in the
table above.
TOTAL COST OF PACKETS OF MEALIE MEAL
900
800
700
600
COST (R)
500
400
300
200
100
0
10
20
30
40
60
NUMBER OF PACKETS OF MEALIE MEAL
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