ملتقى طلاب وطالبات جامعة الملك فيصل,جامعة الدمام - عرض مشاركة واحدة - هنـــــا المراجعه الاخيرة طرق البحث والتصميم

موفق · 2013- 5- 16

69- statistics that are used to show differences or relationship are called
A-between groups
B-one-way ANOVA
C-repeated measures
D-within groups
1- statistics that are used to show differences or relationships are called :
A- descriptive
B- measures
C- inferential
D- parametric
7- on way to make sure that your selection of a research topic is good is to :
A- Do nothing about it and wait until you finish your research
B- you start analysis your data
C- do a literature review

انا هذا حلي والله اعلم

------------------------------------------------------------------------

الاول اخذته من هنا
(b4) Measures of relationship. These quantify the amount of relationship between two (or more) variables as measured in the same group of people or whatever. They are usually on a scale 0-1 (in some instances they run from -1 through 0 to +1). I.e. if such a measure comes out near 1 (or -1 where relevant), that indicates that those cases that scored a particular value on one variable also tended to score a particular value on the other. E.g. those who scored high on motivation also scored high on proficiency. If it comes out near 0, that indicates that cases that scored a particular way on one variable scored all over the other variable, and vice versa. Examples are the Pearson 'r' Correlation Coefficient, the Spearman 'rho' Correlation Coefficient, Kendall's W, the 'phi' Correlation Coefficient, Kruskal's 'gamma'. (Remember that relationship and difference are really the same thing looked at from different points of view. If there is a difference between men and women - the two values of the gender variable - in attitude to RP accent, then there is a relationship between the variables gender and attitude to RP accent. It is just that for technical reasons sometimes statistics approaches the matter more via measuring difference, sometimes via measuring relationship).
If you are only interested in the particular cases or groups of cases you measured in themselves (e.g. because they are the whole population of interest), then (a) and (b) probably provide the answer to any questions or hypotheses you had about them. But usually in research you have not measured everyone/thing of interest directly, but only samples, and wish to generalise, hence inferential statistics are also needed.

2013- 5- 16	#986
موفق أكـاديـمـي ذهـبـي الملف الشخصي: رقم العضوية : 91324 تاريخ التسجيل: Fri Oct 2011 المشاركات: 985 الـجنــس : ذكــر عدد الـنقـاط : 165 مؤشر المستوى: 65 بيانات الطالب: الكلية: الاداب الدراسة: انتساب التخصص: لغة انجليزية المستوى: المستوى الثامن	رد: هنـــــا المراجعه الاخيرة طرق البحث والتصميم 69- statistics that are used to show differences or relationship are called A-between groups B-one-way ANOVA C-repeated measures D-within groups 1- statistics that are used to show differences or relationships are called : A- descriptive B- measures C- inferential D- parametric 7- on way to make sure that your selection of a research topic is good is to : A- Do nothing about it and wait until you finish your research B- you start analysis your data C- do a literature review انا هذا حلي والله اعلم ------------------------------------------------------------------------ الاول اخذته من هنا (b4) Measures of relationship. These quantify the amount of relationship between two (or more) variables as measured in the same group of people or whatever. They are usually on a scale 0-1 (in some instances they run from -1 through 0 to +1). I.e. if such a measure comes out near 1 (or -1 where relevant), that indicates that those cases that scored a particular value on one variable also tended to score a particular value on the other. E.g. those who scored high on motivation also scored high on proficiency. If it comes out near 0, that indicates that cases that scored a particular way on one variable scored all over the other variable, and vice versa. Examples are the Pearson 'r' Correlation Coefficient, the Spearman 'rho' Correlation Coefficient, Kendall's W, the 'phi' Correlation Coefficient, Kruskal's 'gamma'. (Remember that relationship and difference are really the same thing looked at from different points of view. If there is a difference between men and women - the two values of the gender variable - in attitude to RP accent, then there is a relationship between the variables gender and attitude to RP accent. It is just that for technical reasons sometimes statistics approaches the matter more via measuring difference, sometimes via measuring relationship). If you are only interested in the particular cases or groups of cases you measured in themselves (e.g. because they are the whole population of interest), then (a) and (b) probably provide the answer to any questions or hypotheses you had about them. But usually in research you have not measured everyone/thing of interest directly, but only samples, and wish to generalise, hence inferential statistics are also needed.
	التعديل الأخير تم بواسطة موفق ; 2013- 5- 16 الساعة 01:03 PM