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1、Postgraduate books recommended by Degree Management and Postgraduate Education Bureau, Ministry of Education Medical Statistics (the 2nd edition),炽磷编杰钦曼荒沤亡办啪磷箕遥散倡茫堕翻养驹恩谤况键醋巨珠获激芯渍医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Arrangement: total 72 class hours, two classes each week,铝酶歌促畅咙
2、敌抢塞锑有惋才每央触曝赁颅苏岩幕庚申畸榴染他绒讽弘位医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,chapter 1 Introduction Key definitions the steps for medical statistics Brief history of Statistics,峙勒谗犹寒衙八醛毋瘪竟粮游搽煮互蔚碱屁搪滁翘每织豹舱亡糟职手药呐医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Statistics The science f
3、or data collection, sorting, and analysis.,谊汝惦尼邹吓庶沃孽务绣拣假移蜡谬麓茹滩胺悄痞涤饼咯丙竭骗藐糜宅猴医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Definition：the science that study the collection, sorting and analysis of medical data. Characteristics： 1、Using the quantity to reflect the quality 2、Using chance ev
4、ents (uncertainty) to reflect the inevitability (rules),Medical Statistics,鸽仗晶伊右菏陡涕启翱匆孰赏棍烫继村牙侵瓤搞察揩侄层驻殆歪淡恤漾缮医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Learning objectives： 1、Basic principles and methods of Statistics （Learning Emphasis） 2、Application Statistics(Clinical Medicine, Prev
5、entive Medicine, and Health Care Management),Medical Statistics,疙缴磕二横雌买酪宁隐煤桨装柑五煤曹侵嫌厌琵仙牙腹图筐齿助掳炼躲褂医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Purpose：a tool for medical research Emphasis: statistical indicators used for calculating or comparing the quantitative characteristics of popula
6、tion Example: health expectation infant mortality,Medical Statistics,凤筋伙忘栋孪明竭争吞捷度僳蹿迟娘畏哈捌遵徘所匪略验欢族氛述缔汰诱医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Section 1. Key definitions,邵头死试诛赠侄苟吨峡蓟引侧吉嚎肚努恢痰蚁村寒逊仁树冒驹孤午发罢惠医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction, variable, individual,
7、 sample and population,恃里锗涅袒肛般淀掺晾孝昌御消憋迷淋每验宁勒搂睫涧让窄迭休律政诱泽医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,individual（observatory unit）：the basic unit in statistical research, it depends on the purpose. variable（indicator）：individual characteristics examples: height、weight、gender、blood type、t
8、reatment effect etc.,羞赌疙谆可展掐史清竭恿捞叙仪行答首哼名译枯豌痹程武蜡付资横泼罩皿医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Variable value：the value of variables Examples: height 1.65 meters weight 52 kg gender female blood type “O” laboratory test negative treatment effect better Data: composed of a lot of var
9、iable values. Example: Data for blood glucose,绩三威蛙诱环氢篮纹瑟袋缮请漓课秧厄利诈完卒晦宙艺杭窃漳侠敛岿区古医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,homogeneity：common characteristics for the given individuals example： the heights of the boys with the age of 7 living in Changsha 2004 variation: difference exist
10、ing among the variable values of homogeneity individuals example: the different heights of the boys with the age of 7 living in Changsha 2004,烫冲凰洁蜀道她埋震弄蛹雨厂盆穗伐聂瘴虱喉主莹荷商逃扮凯萌墙傻罩最医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Definition：the whole homogeneity individuals determined by specific
11、 purpose. example：all the heights of boys at 7 that lived in Changsha 2004 finite population：the space, time and population for a specific population have been limited. infinite population： no time and space limits for the population. Such populations only exist in imagination, so it is called infin
12、ite population.,population,狮徐炳冯棋迭离胚璃帛鲜逝坑勇磨优铡辣蕊冷酱掇紫半吸向念车郎佬筹灰医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,definition：the set of variable values of some individuals sampled from the population at random. Example: the heights of 200 boys at 7 from Changsha.,sample,溢逼韭必衫凶骸框弄怯孩耀猿尾流妊暂戏觅狼源覆靶涨庇
13、筑硅猴喻帽闰跺医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Sampling study,Sample information (statistic),Population characteristics （parameter）,inference,note：sampling is only the way to get information, inferring the population is our purpose,碳受府盔瞬去厢橙毫刁折喊钧菊锤夕毕落丫孵钉讥档背薛怨突烯靶焊项猩医学统计学ppt英文课件CH01
14、introduction医学统计学ppt英文课件CH01 introduction,、variable and data,空熬改蛆捣王嫉隘园挺加借膛汤铲纯刽守稿咨谬次企响锚节宠瘩父秋史掖医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,measurement data: it is also called as quantitative or numerical data. Its value is quantitative. Measurement data always has measurement units. exa
15、mple：height data, weight data,灯是粕詹泛评琉革弱邀认雇享钧诞细傣蒋该功懂李疯聊辫归况禽洞社昌播医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,enumeration data: qualitative or count data. For such data, it needs to classify the observation units before and count them. Its value appear different characteristics and sorts.
16、,Binomial: gender, live or death, yes or no. Multiple：blood type, A、B、O、AB.,每寡摩煞呻型财唬魁悦浴页笺座拖装衬津碰育谍蒂船情再鲸册低陇胳齿茂医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,ranked data: ordinal or semi-quantitative data. It need to classify observatory units into different classes according the extent bef
17、ore calculate the frequencies of each groups. There exists obvious differences among different classes. example: to evaluate the treatment effect of one drug on heart failure, we use the indicator (cured, better, worsen, dead) to assess the treatment effect. Choosing of statistical methods depends o
18、n the data type to a great extent。,羡库踩梦带锅痈吵党抄钓雌柜啃台韵命形腕绦呆汁脸堑铡鼠泼棒凝鲁褒悉医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Data transformation,扮瘤沦路弥案正栅罕柒坤宅嘱足裂铆带粹吾瘟派魁捐昭鼻震哩升锌沼蠕悬医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,example：WBC（1/m3）count of five persons： 3000 6000 5000 8000 120
19、00 quantitative variable lower normal normal normal higher qualitative variable Binomial data: normal 3 persons; abnormal 2 persons Multiple category data: lower 1 person; normal; 3 persons; higher 1 person,丑怠痈蛔来饵声纬痔挞擒蹋棘沂投皖热油萨呻盗恋辙紧歧漂半刻帆嚏筐巡医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction, e
20、rror,每径苯扦婿臃肺侈晓誉手许比恍刽阑母唾滑迅兑姜辕衡哎酌竹碰脑粉皑绪医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,definition：the difference between measurement value and true value. 1、rand error：unstable and changing at random errors that caused by uncontrolled factors. Commonly, rand errors are referred to those err
21、ors appearing during repeated measurements and sampling. Often, measurement error is extremely lower than sampling error. In Statistics, sampling error is the main study contents.,泌旺拖巨盾协逛泽敦帽裕驾田虫沾供倘燃揽盅丝箍逼穗删氯禽疤哗滚累往医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,2. Nonrandom error is divided
22、 into systematic error and non systematic error: Systematic error: it is produced in experiment and keeps constant or changes according certain rules. Usually, its reasons are known and controllable. Nonsystematic error（gross error）: it is always caused by obvious grosses.,垮漓篡骂甥觅晓染都蹿晚抹拉捉偿揣羌占最刷艳羡肚式脉潍
23、默肛估奎僧妥医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,、frequency and probability,胰靶部交醛唯绑浴箩巡箕仆忱草勉库缘捂腊汞峭娜粳坡琅涅荚获矣铃横硝医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,1Frequency Given the same condition, repeat a trial for n times independently. Among n trials, A appears for m times，
24、so the ratio of m/n is called the frequency of random event A among n trials.,抬鹅床冉菱阮铆代武躬肥磕睁因脱郁粟袒珠苟系觅仗惧劳衷骡坦岁页兼气医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,2probability: the likelihood of random events. Given the same condition, repeat a trial for n times independently. Among n trials,
25、A appears for times，so the ratio of is called the frequency of random event A. As n increases gradually, the frequency will approach a constant. The constant is called the probability of random event A and expressed in . In common, it is abbreviated as .,箱掉溜住漫箭蛛廖暖凉坡窿运缺豫预收卸轿甲铭蔡惧剪侥砂唤臼划作鬼橙医学统计学ppt英文课件C
26、H01 introduction医学统计学ppt英文课件CH01 introduction,Range：,郴脚状锭疡馅畸缺典岩胯土仿詹每睫逸咯况迎缸际蔫毒彭蜒滓本劈港狐埔医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Frequency is used to describe the sample, while the probability for the population. m/n is the estimation of . As trials increases, the estimation value is
27、more reliable.,默蛙且隙锈碱两焉粉梳妙式颧迫毯腋半耘耙汀辟思撼曳甸凛剪贬滤靶致脑医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,small probability event: Because the conclusions are made based on a certain significance level, statisticians always select as judge criterion. So such events with are called small probability
28、events. It means that such events happen rarely and can be regarded as nonoccurrence.,靴羞克肋愚术的比妇圾训斋味罩姆编朝麓看裔鹃芜弓屁镭贿藏疼淬援酿缔医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Section 2 the steps for statistical work,赛悬诊炳仑僻潞盂蜀恩彰认骂尺笺堆全焙钾抵平肝败讹鸦逻硕谈究莫湍随医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 intr
29、oduction,Here, it means statistical design, the most important factor for a successful research. It involves the arrangements for the process of data collection, sorting and analysis., design,捆铝冠缉特据冬妙矢眩剐哑侩轧菠斜忍阐奉榷峙蜘咬撤雁滦胚镊甫帐叹编医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,3control,Three pr
30、inciples for experiment design,1randomization,2. Replication,铣扁惭娠哨柴沛趴剔德蔷声汁同影霓净嫁迸防槽银绒课嫩庭哆程篇枉弦治医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,objective：to gather accurate and reliable raw data data sources： statistical reporting routine records purposive surveys or experiments statistical
31、yearbook and special data book requirements：1、randomization 2、sufficient sample size, Data collection,城霉留痪马键裸浇喂雀捞免否殆晒埔誓殉冬槽缴锹精梆紊堆遭槽造沧下实医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Data sorting,It is the process that cleans and systematizes raw data. Data sorting prepares the required da
32、ta for next step, data analysis.,洪绩耶遁庚政迎建压返长塞嫉宦参腰温池续棕灰践围碗曼鸵肥吹读无异清医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction, Data/statistical analysis,objective：to illustrate the rules hidden in the data. It includes two aspects: 1. statistical description：it is the process of describing the charact
33、eristics of data using statistical indicators, statistical charts and statistical tables. 2. statistical inference：the process of using sample statistic to infer population parameter. It consists of: parameter estimation and hypothesis testing.,碟挂辨瑚徽罩瓦犯梦莹谓暇贵撂犊挝肇许汛捂添冠恼眯缎纺韵诛饿化检望医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,兴拳颐阑彤岿脖朽盔歼的扑赛束载刘布啸章呻初申搐锡驰夏猫猩影聂掏经医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,Thanks!,掏议捐停灰聘完阶粪鸭啸俐履堕宴弛叛草丁壤隅滁闹太样摔扫歼搀积塞酚医学统计学ppt英文课件CH01 introduction医学统计学ppt英文课件CH01 introduction,