**Objectives**

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. A key step in the Statistical Investigation Method is drawing conclusions beyond the observed data. Statisticians often call this “statistical inference.

**Learning Outcomes**

The aim of this course is to provide a strong conceptual foundation of basic statistical inference, with an emphasis on practical aspects of the interpretation.The course deals with the calculation of point estimation and interval estimation at numerical platform. The properties of a good estimator are also discuss in this course. It focuses on testing of hypothesis related to a single population mean, two means. The variety of tests for dependent and independent samples are also considered like z test, paired t test, pooled t test and welch t test. It also involves derivation of power functions of different tests for comparing and evaluation of the tests. Variation plays a vital role in data analysis. So this also covers testing for population variances. The real life application of statistical inference with respect to various field are also the part of this course.

Sr No. | Title | Book |

Week 1 | Basic concept of sampling | Introductory Statistics by P.S Mann |

Week 2 | Estimation and point estimation | Introductory Statistics by P.S Mann |

Week 3 | Interval Estimation and Interval estimation for one and two samples | Introductory Statistics by P.S Mann |

Week 4 | Nature of Hypothesis Testing and Types of errors. | Introductory Statistics by P.S Mann |

Week 5 | Hypothesis Testing for single population mean for population standard deviation known and unknown | Introductory Statistics by P.S Mann |

Week 6 | Hypothesis Testing for two Population Mean for Population Standard deviation known | Introductory Statistics by P.S Mann |

Week 7 | Inferences for the mean of two Normal Populations using Independent Samples (variances are assumed Equal/Not Equal) | Introductory Statistics by P.S Mann |

Week 8 | Inference for Two Populations Mean using Paired Samples. | Introductory Statistics by P.S Mann |

Week 9 | Estimation for Population Proportions. | Introductory Statistics by P.S Mann |

Week 10 | Hypothesis Testing for Population Proportion | Introductory Statistics by P.S Mann |

Week 11 | Estimation for Two Populations | Introductory Statistics by P.S Mann |

Week 12 | Introduction to Chi-Square Test | Introductory Statistics by P.S Mann |

Week 13 | Chi-Square Goodness-of fit Test | Introductory Statistics by P.S Mann |

Week 14 | Chi-Square Independence Tests | Introductory Statistics by P.S Mann |

Week 15 | Inferences for two Population variances | Introductory Statistics by P.S Mann |

Week 16 | 16 Application of statistical inference in different fields | Introductory Statistics by P.S Mann |

Recommended Texts

1. Walpole, R. E., Myers, R. H. & Myers, S. L. (2007). Probability and statistics for engineers and scientists (8th ed.). India: Pearson Prentice Hall.

2. Weiss, N. A. (2017). Introductory statistics. (10th ed.). United States: Pearson Education.

**Assessment Criteria:**

Exam:Mid(30%),Final(50%),

Sessional(20%):Assignment,Presentations,Class Participation,Quizzes

**Time Table: **BS Regualr

Monday(09:00 to 10:00 AM)

Tuesday(09:00 to 10:00 AM)

Wednesday(11:00 to 12:00 AM)

BS-Self Support

Monday(03:00 PM to 04:00 PM)

Tuesday( 02:00 PM to 03:00 PM)

Thursday(03:00 PM to 04:00 PM)