{"id":1112,"date":"2023-03-23T05:47:48","date_gmt":"2023-03-23T11:47:48","guid":{"rendered":"https:\/\/smdlearning.com\/product\/stats-principles-in-medical-devices\/"},"modified":"2025-08-07T15:29:41","modified_gmt":"2025-08-07T21:29:41","slug":"stats-principles-in-medical-devices","status":"publish","type":"product","link":"https:\/\/smdlearning.com\/product\/stats-principles-in-medical-devices\/","title":{"rendered":"Stats Principles in Medical Devices"},"content":{"rendered":"<p>Stats Principles in Medical Devices is a course designed to proportionate the students with hands-on understanding of basic statistics tools.<\/p>\n<p><span style=\"color: #004f71;\"><strong>Duration:<\/strong><\/span> 12 hours<\/p>\n<p><span style=\"color: #004f71;\"><strong>CEUs: <\/strong><\/span>1.35<\/p>\n<p><span style=\"color: #004f71;\"><strong>Modality:<\/strong><\/span>\u00a0Group<\/p>\n<p><span style=\"color: #004f71;\"><strong>Participant limit:<\/strong><\/span>\u00a015<\/p>\n<p><b><a href=\"https:\/\/smdacademy.smdlearning.com\/pluginfile.php\/181\/course\/summary\/Stats_Principles.pdf?time=1707423394961\" target=\"_blank\" rel=\"noopener\">Download Course Technical Information<\/a><\/b><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Stats Principles \u00a0in Medical Devices is a course designed to provide students with hands-on understanding of basic statistics tools.\u00a0 Central tendency metrics, dispersion analysis, distribution fit, hypothesis testing and graphs creation and interpretation are tools that allow students to describe and compare data behaviors, identify desirable and undesirable conditions related with the process or data collection procedure.\u00a0 Appropriate data description and analysis are the first step in many mayors decision-making processes in the Medical Devices Industry, consequently, it becomes crucial knowledge for engineers in the industry. This course is given with the support of software traditionally used in this industry and based on application cases.<\/p>\n<h4>At The End Of The Course You Will Be Able To<\/h4>\n<ul>\n<li>Know main concepts required for data collection and statistical analysis.<\/li>\n<\/ul>\n<ul>\n<li>Use and interpret descriptive metrics such as mean, mode, median, variance, standard deviation, quartile, percentile, and range.<\/li>\n<\/ul>\n<ul>\n<li>Fit data to probability distributions.<\/li>\n<\/ul>\n<ul>\n<li>Understand basic distributions characteristics and how it helps to describe the data under analysis using well known probability distributions.<\/li>\n<\/ul>\n<ul>\n<li>Use of graphs to describe and rationalize data behaviors.<\/li>\n<\/ul>\n<ul>\n<li>Recognize the graphs that are better fit to use under different situations.<\/li>\n<\/ul>\n<ul>\n<li>Use graphs to recognize suspicious data behaviors or data collection mistakes that could affect the data credibility, for instance outliers, data from mixed populations, truncated data or rounding problems.<\/li>\n<\/ul>\n<ul>\n<li>Identify if a sample mean is statistically similar or not to a reference value through hypothesis testing.<\/li>\n<\/ul>\n<ul>\n<li>Make decisions through the interpretation of data from applied examples.<\/li>\n<\/ul>\n<h4 class=\"subtitle\">Course Content<\/h4>\n<ol>\n<li>Introduction to statistics and basic concepts\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Introduction to statistics and basic concepts<\/span>\n<ul>\n<li>General concepts<\/li>\n<li>Bias<\/li>\n<li>Population and sample<\/li>\n<li>Skewness<\/li>\n<li>Kurtosis<\/li>\n<li>p-value<\/li>\n<li>Random Variables<\/li>\n<\/ul>\n<\/li>\n<li>Descriptive Statistics\n<ul>\n<li>Central tendency metrics<\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Mean<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Median<\/span><\/li>\n<li>Mode<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li>Variability Metrics\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Standard deviation<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Variance<\/span><\/li>\n<li>Percentiles and quartiles<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Inference statistics<\/span>\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Central limit theorem<\/span>\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Hypothesis test<\/span>\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">One Tailed<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Bilateral<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Paired Observations<\/span><\/li>\n<li>Normality test<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li>Graphs and distributions<\/li>\n<li>Commonly used graph for data analysis\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Histogram<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Boxplot<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Bar Chart<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Individual plot<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Interval<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Time series<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Scatter plots<\/span><\/li>\n<\/ul>\n<\/li>\n<li>Commonly used Distributions<\/li>\n<\/ol>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Discrete<\/span>\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Uniform<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Bernoulli<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Binomial<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Negative Binomial<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Geometric<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Poisson<\/span><\/li>\n<\/ul>\n<\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Continuous<\/span>\n<ul>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Uniform<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Exponential<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Chi- square<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Gamma<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Beta<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Weibull<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Normal<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">Log-Normal<\/span><\/li>\n<li><span lang=\"en-us\" xml:lang=\"en-us\">T-student<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n","protected":false},"featured_media":762,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false},"product_cat":[26],"product_tag":[],"class_list":{"0":"post-1112","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-statisticsformedicaldevicesmanufacturing","8":"first","9":"instock","10":"downloadable","11":"virtual","12":"taxable","13":"product-type-simple"},"acf":[],"_links":{"self":[{"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/product\/1112","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/comments?post=1112"}],"version-history":[{"count":4,"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/product\/1112\/revisions"}],"predecessor-version":[{"id":2479,"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/product\/1112\/revisions\/2479"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/media\/762"}],"wp:attachment":[{"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/media?parent=1112"}],"wp:term":[{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/product_cat?post=1112"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/smdlearning.com\/wp-json\/wp\/v2\/product_tag?post=1112"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}