College Enrollment Figures

College Enrollment Figures September 20, 2013 Hispanic Americans and women are on the rise across American college campuses. Marketing Charts has some interesting college enrollment figures. According to an article on college enrollment numbers in Marketing Charts, After growing by 3.2 million between 2006 and 2011, the number of Americans enrolled in college (undergraduate and graduate) fell by almost half-a-million last year to 19.9 million, or 6.7% of the population aged 3 and up, according to recent figures released by the US Census Bureau. The data tables contain some interesting demographic statistics on college students, who are estimated to command $117 billion in discretionary spending power. Of the college enrollment figure findings, there are many more females enrolled in colleges than males (11.3 million as compared to 8.6 million). The number of Caucasian American  and African Americans enrolled in colleges has declined, while more Hispanic Americans are going to college  (11% of the total college population in 2006 as compared to 17% of the total population last year). Asian Americans have the highest enrollment rate. And get this there were 40 fourteen or fifteen year-olds enrolled in college last year. How many of these students would you conjecture attend Harvard or MIT? Let us know your thoughts by posting  a Comment below! We look forward to hearing from you.

Variables May Have an Influence on the Dependent Variable - 275 Words

Extraneous Variables May Have an Influence on the Dependent Variable (Research Paper Sample) Content: Extraneous Variables May Have an Influence on the Dependent VariableStudent NameInstitutionExtraneous Variables May Have an Influence on the Dependent VariableTo control extraneous variables researchers first identify those variables that have a high likelihood of influencing the dependent variable. This is based on their experience, simple logical reasoning, and common sense. Furthermore, once identified the extraneous variable can be controlled by either matching values across treatment conditions or holding a variable constant. The extraneous variables can be held constant by creating a standardized procedure and environment thus making all variables the same in each condition and hence they cannot be confounding ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1177/105382590803100305", "ISBN" : "1053-8259", "ISSN" : "1053-8259", "abstract" : "There is an increasing interest in the field of experiential education to move beyond simply documenting the value of experiential education programs and, instead, develop more evidence-based models for experiential educa- tion practice (cf., Gass, 2005; Henderson, 2004). Due in part to the diversity of experiential education programs, participants, goals, designs, and specific program experiences, there exists a broad constellation of variables that can impact the results of studies using an evidence-based approach. While many of these variables are accounted for through effective research designs, oth- ers are largely uncontrollable, yet remain influential. These uncontrollable variables can often distort or confound the results from research and evalu- ation efforts. This paper categorizes some of the most common confounding variables into three temporally based categories: Precursor, Concomitant, and Postexperience. Following this, suggestions for researchers and evaluators in addressing these variables are provided.", "author" : [ { "dropping-particle" : "", "f amily" : "Ewert", "given" : "Alan", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Sibthorp", "given" : "Jim", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Journal of Experiential Education", "id" : "ITEM-1", "issue" : "3", "issued" : { "date-parts" : [ [ "2009" ] ] }, "page" : "376-389", "title" : "Creating Outcomes Through Experiential Education: The Challenge of Confounding Variables", "type" : "article-journal", "volume" : "31" }, "uris" : [ "/documents/?uuid=846ca279-098c-4a81-9665-b68c278845dd" ] } ], "mendeley" : { "formattedCitation" : "(Ewert Sibthorp, 2009)", "plainTextFormattedCitation" : "(Ewert Sibthorp, 2009)", "previouslyFormattedCitation" : "(Ewert and Sibthorp 2009)" }, "properties" : { "noteIndex" : 0 }, "schema" : "https://github.com/citation-style-language/schema/raw/master/csl-citation.json" }(Ewert Sibthorp, 2009). Through matching the values across treatment conditions the researcher ensure that the variable cannot vary across the treatment conditions. A good example of this is when participants are assigned ensuring that the average age is the same across all different treatment conditions.Random assignment is another technique that can be used to control extraneous variables since it can control both unknown and known confounding extraneous variables. Therefore, the researcher should randomly assign wherever and whenever possible. Random assignment ensures that all groups are similar during the start of the experiment since each group has an equal chance of being selected ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1177/105382590803100305", "ISBN" : "1053-8259", "ISSN" : "1053-8259", "abstract" : "There is an increasing interest in the field of experiential education to move beyond simply documenting the value of experiential education programs and, instead, develop more evidence-b ased models for experiential educa- tion practice (cf., Gass, 2005; Henderson, 2004). Due in part to the diversity of experiential education programs, participants, goals, designs, and specific program experiences, there exists a broad constellation of variables that can impact the results of studies using an evidence-based approach. While many of these variables are accounted for through effective research designs, oth- ers are largely uncontrollable, yet remain influential. 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If successful, the groups will be like mirror images of each other.Matching also controls for extraneous variables by linking the compar ison groups on one or more variables which are correlated with the dependent variable. First, the researcher has to decide which extraneous variables he wants to match on (that is, deciding what specific variables he wants to make his groups similar on). Such variables that the researcher decides to use are known as matching variables ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1177/105382590803100305", "ISBN" : "1053-8259", "ISSN" : "1053-8259", "abstract" : "There is an increasing interest in the field of experiential education to move beyond simply documenting the value of experien...