H�T�Mo�0���>v�!|��J��$����N�aH#D���q�i�'�����U�T�a�&{�����i ��� N��r;m���O�y��v�E��]�K���9}�@����z؝��/ 2500 staff attended) is a good example of simple random sampling. endstream 14 0 obj <> endobj Author content. 4 . Introduction The aim of this article is to discuss about the sampling and sampling technicality. %PDF-1.5 [Raj, p4] The surveyor’s (a person or a establishment in charge of collecting and recording data) or researchers initial task is to formulate a rational justification for the use of sampling in his research. 10 0 obj 2. 7 0 obj %���� The populationis the entire group that you want to draw conclusions about. �an� P����j�5�a��G��t��Ӄ�H�x�����WGF�? �V�pD�@e -vJW/�mF�e���#$�9�O-ξ��#ITBq�J@���SF*.��n���(��8Έ�ǍiS�6̹p��$��"���]_��@I�T�rL�7"S K��t�g�\L9�X�\^j*~��A,�b��c�7Ϯ!P_�Ym��� �����>�~ ɑ� endstream endobj 94 0 obj << /Type /FontDescriptor /Ascent 761 /CapHeight 716 /Descent -176 /Flags 4 /FontBBox [ -103 -213 1177 926 ] /FontName /BJCPCI+MetaPlusBook-Roman /ItalicAngle 0 /StemV 92 /XHeight 536 /StemH 20 /CharSet (/I/n/t/r/o/d/u/c/i/space/S/a/m/p/l/g/F/e/seven/period/one/A/B/C/two/D/E/\ eight/slash/four/five/nine/six/plus/three/parenleft/percent/parenright/h\ yphen/zero/endash/asterisk/b/y/v/R/f/s/comma) /FontFile3 100 0 R >> endobj 95 0 obj << /Type /Font /Subtype /Type1 /FirstChar 32 /LastChar 144 /Widths [ 225 500 500 500 500 838 500 500 500 500 482 500 267 338 267 500 548 416 541 509 548 494 561 459 600 564 500 500 500 500 500 500 500 580 612 548 636 536 500 500 649 314 500 615 500 845 500 668 577 666 607 584 518 500 590 856 500 500 500 500 500 500 500 500 500 516 547 440 552 510 310 552 558 274 279 514 303 792 542 527 544 550 352 472 334 532 468 712 501 497 456 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 267 ] /Encoding 96 0 R /BaseFont /BJCPCH+MetaPlusBold-Roman /FontDescriptor 99 0 R /ToUnicode 98 0 R >> endobj 96 0 obj << /Type /Encoding /Differences [ 32 /space 37 /percent 42 /asterisk 44 /comma /hyphen /period 48 /zero /one /two /three /four /five /six /seven /eight /nine 65 /A /B /C /D /E 72 /H /I 75 /K 77 /M 79 /O /P /Q /R /S /T 86 /V /W 97 /a /b /c /d /e /f /g /h /i /j /k /l /m /n /o /p /q /r /s /t /u /v /w /x /y /z 144 /quoteright ] >> endobj 97 0 obj << /Filter /FlateDecode /Length 5148 /Subtype /Type1C >> stream stream Enough information is included here for the user to understand the basic concepts and relationships in HS sampling to apply <> endobj An Introduction to Headspace Sampling in Gas Chromatography Introduction This document is intended to provide the newcomer to headspace sampling with a concise summary of the theory and principles of this exciting technique. endobj F��+�88x[N1�l�``�����(� ��o�ρ��LK“�;G��f�� �צ� endstream endobj 114 0 obj 466 endobj 90 0 obj << /Type /Page /Parent 73 0 R /Resources 91 0 R /Contents 103 0 R /MediaBox [ 0 0 360 576 ] /CropBox [ 0 0 360 576 ] /Rotate 0 >> endobj 91 0 obj << /ProcSet [ /PDF /Text ] /Font << /F1 104 0 R /F2 95 0 R /F3 102 0 R /F4 107 0 R >> /ExtGState << /GS1 110 0 R /GS2 108 0 R >> /ColorSpace << /Cs6 101 0 R >> >> endobj 92 0 obj << /Type /Encoding /Differences [ 32 /space 37 /percent 40 /parenleft /parenright /asterisk /plus /comma /hyphen /period /slash /zero /one /two /three /four /five /six /seven /eight /nine 65 /A /B /C /D /E /F 73 /I 82 /R /S 97 /a /b /c /d /e /f /g 105 /i 108 /l /m /n /o /p 114 /r /s /t /u /v 121 /y 133 /endash ] >> endobj 93 0 obj << /Filter /FlateDecode /Length 301 >> stream 8 0 obj T�wN-h=d/uB_��qx��Jƣ �Fa�ض�J�}��9�Uif���8^���EX��a�� ��֛S��Z䅉���A�p���@ry���Zs4Uݖ�rrC'�M�,(��x�b������Fez�~Rs��-�~���Ь���e\�%'}`�JydRS����N�+y>%�ݽ���755^lE-��xĪ��ګ h�s�z?����;�����[B�"���9�Pr/Y��gc���n��K��M���Q�D_��,/�������l#6��|Km ���$��x��/��=�6�ǿ�TJ���y�oQ�����v�[;���I�t�N�9�����Q��&'C�ۍ)�!�Ъf ��c�,�_u�_̯��2�r�4��&(�re� vĕ��q�L/^���,�� �XS|������Y�='���ʤ�}f���k; �v泍s���w&�N5��Ղ�9Q[��v߭�ǖƑ��'3F�'����ތV/��+7��M��+13����:��ۣ�\�%����bM����GD��L��chH*t�r�5l�xŘ���j���������Ajk��lyk۲�R�Ux��!�T�&�v���S �j�����^�8P���:kF2Ս�}\`"\������A�:���T�>ux-yj�����������l��Αq�7jF�[K1ne��35-�jf`1\ċ�r$� All content in … x��Z[��H~���P���&��R��t&��j3�U�ڇ�>`�c��b��w���T�m쬢V0U�����o���ݗ��ӓx��x���ͻO��C�����'\���w\�o'�ŷ��5���o\�~����o�����~�����Ͽ��~Vb���o����/�~�;���ǯ��o{��#)>~� �E�gѣ���q���a���3�|�W��=' 10. endobj Sampling is a procedure, where in a fraction of the data is taken from a large set of data, and the inference drawn from the sample is extended to whole group. b���Ϥi�^�X���Q�^M�=Nt]#5�¢��|9�[�7���A.�'��Ia����8���]�)�ͩ�0���'B�u�g����¹�?�f5Ue�ҋ�ب^vSx��z�#*��n��)��z���w:�'����X�z��A���w�^]4�F@��\\����V6��4�aZ� �DOe�/uo���̃�я��є�vg>rH��� <> endobj 1 Introduction One crucial aspect of study design is deciding how big your sample should be. <> INTRODUCTION •Why do scientists need to know about:-1)Experimental design?-2) Sampling techniques ?-3) Statistics? Sampling 62–70 10.1 Introduction 62 10.2 Definitions 62 10.3 Types of Population62 10.4 Sample 63 10.5 Sam pling Variation and Bias 64 10.6 Nonprobability Sampling Techniques 65 10.7 Probability (Random) Sampling Techniques 65 10.8 Listing of Population 69 10.9 Sample Size 69 Questions 70 11. Example: The Literary Digest and Presidential Elections . *�R�K�������D*B�ĔeF�MސO�WYjO�M0��xR�p�c��I�(����L�̙��L�O�GZ�["L&���#2�(R�����d�1�ڵ+DA����>���ض9��\�'mK���H�)�гI��T`e�=ev>H��&5�JJ��d�in��_n�~ꤑU4NQM%�k�j�n�8Ɋ •Each individual is chosen randomly and each member of the population has an equal chance of being included in the sample. <> PROF. DR. MOHD ROSNI SULAIMAN FACULTY OF FOOD SCIENCE AND NUTRITION UNIVERSITI MALAYSIA SABAH. SAMPLING TECHNIQUES Basic concepts of sampling Essentially, sampling consists of obtaining information from only a part of a large group or population so as to infer about the whole population. <> endobj <> • The steps you must apply to put your sampling plan into action. ����(SP`P@ �l‘�-k&� -����Sgf�k`�`�� ��l�0���H �6[�%� 1 0 obj 2 0 obj Describe a sampling distribution in terms of “all possible outcomes” 4. Content uploaded by Hamed Taherdoost.

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