The Purpose Of Statistics In The Criminological Sciences

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Question #1: Explain the following key term in Chapter 1
(a) Causal validity: It is the approximate truth about the inferences about causal relationships.
(b) Element: An element is a data unit for which the definition, identification, and representation values are specified using a set of attributes.
(c) Generalizability: This is about the conceptualization, investigation, and design of reliable observations.
(d) Generalizations: in statistics, it is a case where, from a limited sample, conclusions are extended to a whole population containing all the units that could be observable.
(e) Hypothesis: A hypothesis in statistics is a statement that needs to be tested through research or experimentation to determine if it is true of false.
(f) Inferences: Inference in Statistics is the process of determining the properties of an underlying distribution through data analysis.
(g) Inferential statistics: inferential statistics are the methods that enable one to use some samples to make generalizations for the entire population from which the samples are drawn.
(h) Internal validity: ...
... This is the approximate truth regarding inferences of causal 9or cause and effect) relationships.
(i) Non-probability sampling methods: The non-probability sampling methods do not entail a random selection of samples.
(j) Population: In statistics, the population is used to mean the sample about which the study is taking place.
(k) Population parameter: this is a statistical measure or quantity that, for a particular sample, is fixed and it acts as a value of a variable for a given general distribution to make it descriptive of the sample.
(l) Probability sampling methods: These techniques involve a random selection of research participants.
(m) Random selection: in random sampling, all the objects have the same probability of being chosen for incorporation in the survey.
(n) Sample: It is a subset of individuals from a given population who will be used in estimating the characteristics of the entire population.
(o) Sample statistic: A sample statistic, also referred to as a statistic, is a single measure of an attribute of a sample.
(p) Sampling error: This is the error resulting from a sample observation instead of a population observation.
(q) Validity: this is the degree to which an idea, conclusion or measurement corresponds to the real world.

Question #2: Define and Understand Descriptive Research in Criminal Justice
In the study case “The magnitude of youth violence,” the descriptive research is about the epidemic of youth violence and its persistence over the years. It answers the questions about how youth violence is an ongoing, startling, and pervasive problem. Through the descriptive statistics, the case describes the magnitude of as well as the trends in violent crime by the youth, focusing on aggravated assault, forcible rape, homicide, and robbery.
 
Question #3: Define and Understand Explanatory Research
In the case study, causes of youth violence, the explanatory research involves the explanation of the things that drive the youth to become violent. There is also an explanation of the variations in violence between the youths of various genders and age. The case also explains the reasons as to why crime seems to be prevalent among the youth. These all represent explanatory research because they explain a given phenomenon.

Question #4: Define and Understand Evaluation Research
The evaluation research in the case study, School Programs to Prevent Youth Violence is about the programs that have been enacted the school in question with the aim of combating violence. The case study talks about the way various parties can join hands to develop strong programs for mitigating youth violence. It is about the steps that can be undertaken to ensure that youth violence is contained as the youth learn how to live harmoniously with others.

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