Why is BioStatistics a basic foundation in decision-making?
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A: It is an important part of statistics. It is widely used.
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Q: Why is Biostatistics an integral part of the basic foundation in decision making
A: Definition: Biostatistics: It is branch of applied statistics and has very useful…
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- Cholesterol Cholesterol in human blood is necessary, but too much can lead to health problems. There are three main types of cholesterol: HDL (high-density lipoproteins), LDL (low-density lipoproteins), and VLDL (very low-density lipoproteins). HDL is considered “good” cholesterol; LDL and VLDL are considered “bad” cholesterol. A standard fasting cholesterol blood test measures total cholesterol, HDL cholesterol, and triglycerides. These numbers are used to estimate LDL and VLDL, which are difficult to measure directly. Your doctor recommends that your combined LDL/VLDL cholesterol level be less than 130 milligrams per deciliter, your HDL cholesterol level be at least 60 milligrams per deciliter, and your total cholesterol level be no more than 200 milligrams per deciliter. (a) Write a system of linear inequalities for the recommended cholesterol levels. Let x represent the HDL cholesterol level, and let y represent the combined LDL VLDL cholesterol level. (b) Graph the system of inequalities from part (a). Label any vertices of the solution region. (c) Is the following set of cholesterol levels within the recommendations? Explain. LDL/VLDL: 120 milligrams per deciliter HDL: 90 milligrams per deciliter Total: 210 milligrams per deciliter (d) Give an example of cholesterol levels in which the LDL/VLDL cholesterol level is too high but the HDL cholesterol level is acceptable. (e) Another recommendation is that the ratio of total cholesterol to HDL cholesterol be less than 4 (that is, less than 4 to 1). Identify a point in the solution region from part (b) that meets this recommendation, and explain why it meets the recommendation.Why is Biostatistics an integral part of the basic foundation in decision making?List and explain all three classes of decision making?
- variables and hypothesis section: The article reviews various aspects of network analysis and probabilistic inference to understand the complexities and dynamics of network analysis. It utilizes data from clinical education on diabetic foot and online social network software to analyze the relationships between network participants and the patterns related to their networking behavior. The data explored involve clinical education on diabetic foot and online and social network software for research. The variables being analyzed are the relationships between the network participants, as well as the patterns related to the networking behaviors. The hypotheses tested in the article are related to examining the effect of different forms of networks on the efficacy of clinical education, as well as the impact of online network relationships among people. The outcomes of the analysis and hypotheses in the article are used to explain the importance of different probabilistic inferences and…Is it possible to have several dependent variables in a model? Are several variables possible in a decision-making problem? Which model—descriptive, predictive, or prescriptive—of a particular choice issue would you be most likely to employ if it were offered to you? Why? Give an example of a well-known corporate, political, or military leader who made a choice that either had a positive or negative impact. What distinguishes a computer model from a spreadsheet model?Why is strategic competency important?
- Which is the best option help??A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is the null hypothesis?A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What do the results of this study mean to you?
- A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. Is there significance for either gender or income?A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is one research hypothesis (there are three possible hypotheses here – name them all if you can.A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is one research hypothesis (there are three possible hypotheses here name them all if you can but naming at least one is required)?